Merge pull request #615 from trycua/fix/remove-deprecated-models

Remove `claude-3-5-sonnet-20241022`
2026-01-01 19:10:30 -06:00 · 2025-11-23 16:31:13 -05:00
parent 90a1cf01ad 1bc43aa83b
commit 606ba6fb11
38 changed files with 92 additions and 88 deletions
--- a/README.md
+++ b/README.md
@@ -242,7 +242,7 @@ agent = ComputerAgent(model="huggingface-local/HelloKKMe/GTA1-7B+openai/gpt-5")
 agent = ComputerAgent(model="omniparser+openai/gpt-4o")

 # Combine state-of-the-art grounding with powerful reasoning
-agent = ComputerAgent(model="huggingface-local/HelloKKMe/GTA1-7B+anthropic/claude-3-5-sonnet-20241022")
+agent = ComputerAgent(model="huggingface-local/HelloKKMe/GTA1-7B+anthropic/claude-sonnet-4-5-20250929")

 # Combine two different vision models for enhanced capabilities
 agent = ComputerAgent(model="huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B+openai/gpt-4o")
--- a/blog/app-use.md
+++ b/blog/app-use.md
@@ -25,7 +25,7 @@ desktop = computer.create_desktop_from_apps(["Safari", "Notes"])

 # Your agent can now only see and interact with these apps
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[desktop]
 )
 ```
@@ -94,7 +94,7 @@ async def main():

    # Initialize an agent
    agent = ComputerAgent(
-        model="anthropic/claude-3-5-sonnet-20241022",
+        model="anthropic/claude-sonnet-4-5-20250929",
        tools=[desktop]
    )

@@ -160,7 +160,7 @@ async def automate_iphone():

    # Initialize an agent for iPhone automation
    agent = ComputerAgent(
-        model="anthropic/claude-3-5-sonnet-20241022",
+        model="anthropic/claude-sonnet-4-5-20250929",
        tools=[my_iphone]
    )

--- a/blog/build-your-own-operator-on-macos-2.md
+++ b/blog/build-your-own-operator-on-macos-2.md
@@ -145,9 +145,9 @@ While the core concept remains the same across all agent loops, different AI mod
 | Agent Loop | Supported Models | Description | Set-Of-Marks |
 |:-----------|:-----------------|:------------|:-------------|
 | `AgentLoop.OPENAI` | • `computer_use_preview` | Use OpenAI Operator CUA Preview model | Not Required |
-| `AgentLoop.ANTHROPIC` | • `claude-3-5-sonnet-20240620`<br>• `claude-3-7-sonnet-20250219` | Use Anthropic Computer-Use Beta Tools | Not Required |
+| `AgentLoop.ANTHROPIC` | • `claude-sonnet-4-5-20250929`<br>• `claude-3-7-sonnet-20250219` | Use Anthropic Computer-Use Beta Tools | Not Required |
 | `AgentLoop.UITARS` | • `ByteDance-Seed/UI-TARS-1.5-7B` | Uses ByteDance's UI-TARS 1.5 model | Not Required |
-| `AgentLoop.OMNI` | • `claude-3-5-sonnet-20240620`<br>• `claude-3-7-sonnet-20250219`<br>• `gpt-4.5-preview`<br>• `gpt-4o`<br>• `gpt-4`<br>• `phi4`<br>• `phi4-mini`<br>• `gemma3`<br>• `...`<br>• `Any Ollama or OpenAI-compatible model` | Use OmniParser for element pixel-detection (SoM) and any VLMs for UI Grounding and Reasoning | OmniParser |
+| `AgentLoop.OMNI` | • `claude-sonnet-4-5-20250929`<br>• `claude-3-7-sonnet-20250219`<br>• `gpt-4.5-preview`<br>• `gpt-4o`<br>• `gpt-4`<br>• `phi4`<br>• `phi4-mini`<br>• `gemma3`<br>• `...`<br>• `Any Ollama or OpenAI-compatible model` | Use OmniParser for element pixel-detection (SoM) and any VLMs for UI Grounding and Reasoning | OmniParser |

 Each loop handles the same basic pattern we implemented manually in Part 1:

@@ -191,7 +191,7 @@ The performance of different Computer-Use models varies significantly across tas

 - **AgentLoop.OPENAI**: Choose when you have OpenAI Tier 3 access and need the most capable computer-use agent for web-based tasks. Uses the same [OpenAI Computer-Use Loop](https://platform.openai.com/docs/guides/tools-computer-use) as Part 1, delivering strong performance on browser-based benchmarks.

- **AgentLoop.ANTHROPIC**: Ideal for users with Anthropic API access who need strong reasoning capabilities with computer-use abilities. Works with `claude-3-5-sonnet-20240620` and `claude-3-7-sonnet-20250219` models following [Anthropic's Computer-Use tools](https://docs.anthropic.com/en/docs/agents-and-tools/computer-use#understanding-the-multi-agent-loop).
+- **AgentLoop.ANTHROPIC**: Ideal for users with Anthropic API access who need strong reasoning capabilities with computer-use abilities. Works with `claude-sonnet-4-5-20250929` and `claude-3-7-sonnet-20250219` models following [Anthropic's Computer-Use tools](https://docs.anthropic.com/en/docs/agents-and-tools/computer-use#understanding-the-multi-agent-loop).

 - **AgentLoop.UITARS**: Best for scenarios requiring more powerful OS/desktop, and latency-sensitive automation, as UI-TARS-1.5 leads in OS capabilities benchmarks. Requires running the model locally or accessing it through compatible endpoints (e.g. on Hugging Face).

--- a/blog/composite-agents.md
+++ b/blog/composite-agents.md
@@ -14,12 +14,12 @@ This is the kind of problem that makes you wonder if we're building the future o

 Agent framework 0.4 solves this by doing something radical: making all these different models speak the same language.

-Instead of writing separate code for each model's peculiarities, you now just pick a model with a string like `"anthropic/claude-3-5-sonnet-20241022"` or `"huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B"`, and everything else Just Works™. Behind the scenes, we handle all the coordinate normalization, token parsing, and image preprocessing so you don't have to.
+Instead of writing separate code for each model's peculiarities, you now just pick a model with a string like `"anthropic/claude-sonnet-4-5-20250929"` or `"huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B"`, and everything else Just Works™. Behind the scenes, we handle all the coordinate normalization, token parsing, and image preprocessing so you don't have to.

 ```python
 # This works the same whether you're using Anthropic, OpenAI, or that new model you found on Hugging Face
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",  # or any other supported model
+    model="anthropic/claude-sonnet-4-5-20250929",  # or any other supported model
    tools=[computer]
 )
 ```
--- a/blog/hud-agent-evals.md
+++ b/blog/hud-agent-evals.md
@@ -58,7 +58,7 @@ await run_full_dataset(
 # Or test on SheetBench (50 spreadsheet tasks)
 await run_full_dataset(
    dataset="hud-evals/SheetBench-V2",
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    split="train[:2]"
 )
 ```
--- a/docs/content/docs/agent-sdk/agent-loops.mdx
+++ b/docs/content/docs/agent-sdk/agent-loops.mdx
@@ -34,7 +34,7 @@ async def take_screenshot():
    ) as computer:

        agent = ComputerAgent(
-            model="anthropic/claude-3-5-sonnet-20241022",
+            model="anthropic/claude-sonnet-4-5-20250929",
            tools=[computer],
            max_trajectory_budget=5.0
        )
@@ -121,7 +121,7 @@ The output is an AsyncGenerator that yields response chunks.
 The `ComputerAgent` constructor provides a wide range of options for customizing agent behavior, tool integration, callbacks, resource management, and more.

 - `model` (`str`): Default: **required**
-  The LLM or agent model to use. Determines which agent loop is selected unless `custom_loop` is provided. (e.g., "claude-3-5-sonnet-20241022", "computer-use-preview", "omni+vertex_ai/gemini-pro")
+  The LLM or agent model to use. Determines which agent loop is selected unless `custom_loop` is provided. (e.g., "claude-sonnet-4-5-20250929", "computer-use-preview", "omni+vertex_ai/gemini-pro")
 - `tools` (`List[Any]`):
  List of tools the agent can use (e.g., `Computer`, sandboxed Python functions, etc.).
 - `custom_loop` (`Callable`):
@@ -159,7 +159,7 @@ from computer import Computer
 from agent.callbacks import ImageRetentionCallback

 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[Computer(...)],
    only_n_most_recent_images=3,
    callbacks=[ImageRetentionCallback(only_n_most_recent_images=3)],
--- a/docs/content/docs/agent-sdk/callbacks/cost-saving.mdx
+++ b/docs/content/docs/agent-sdk/callbacks/cost-saving.mdx
@@ -13,7 +13,7 @@ Optimize agent costs with budget management and image retention callbacks.
 from agent.callbacks import BudgetManagerCallback

 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    callbacks=[
        BudgetManagerCallback(
@@ -30,7 +30,7 @@ agent = ComputerAgent(
 ```python
 # Simple budget limit
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    max_trajectory_budget=5.0  # $5 limit
 )
 ```
@@ -40,7 +40,7 @@ agent = ComputerAgent(
 ```python
 # Advanced budget configuration
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    max_trajectory_budget={
        "max_budget": 10.0,
        "raise_error": True,  # Raise error when exceeded
@@ -55,7 +55,7 @@ agent = ComputerAgent(
 from agent.callbacks import ImageRetentionCallback

 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    callbacks=[
        ImageRetentionCallback(only_n_most_recent_images=3)
@@ -67,7 +67,7 @@ agent = ComputerAgent(

 ```python
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    only_n_most_recent_images=3  # Auto-adds ImageRetentionCallback
 )
@@ -77,7 +77,7 @@ agent = ComputerAgent(

 ```python
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    max_trajectory_budget=5.0,        # Budget limit
    only_n_most_recent_images=3,      # Image retention
--- a/docs/content/docs/agent-sdk/callbacks/index.mdx
+++ b/docs/content/docs/agent-sdk/callbacks/index.mdx
@@ -21,7 +21,7 @@ from agent.callbacks import (
 )

 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    callbacks=[
        ImageRetentionCallback(only_n_most_recent_images=3),
--- a/docs/content/docs/agent-sdk/callbacks/logging.mdx
+++ b/docs/content/docs/agent-sdk/callbacks/logging.mdx
@@ -14,7 +14,7 @@ from agent.callbacks import LoggingCallback
 import logging

 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    callbacks=[
        LoggingCallback(
@@ -29,7 +29,7 @@ agent = ComputerAgent(

 ```python
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    verbosity=logging.INFO  # Auto-adds LoggingCallback
 )
@@ -72,7 +72,7 @@ class CustomLogger(AsyncCallbackHandler):

 # Use custom logger
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    callbacks=[CustomLogger("my_agent")]
 )
--- a/docs/content/docs/agent-sdk/callbacks/trajectories.mdx
+++ b/docs/content/docs/agent-sdk/callbacks/trajectories.mdx
@@ -13,7 +13,7 @@ The TrajectorySaverCallback records complete agent conversations including messa
 from agent.callbacks import TrajectorySaverCallback

 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    tools=[computer],
    callbacks=[
        TrajectorySaverCallback(
@@ -28,7 +28,7 @@ agent = ComputerAgent(

 ```python
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    trajectory_dir="trajectories",  # Auto-save trajectories
    tools=[computer]
 )
--- a/docs/content/docs/agent-sdk/migration-guide.mdx
+++ b/docs/content/docs/agent-sdk/migration-guide.mdx
@@ -7,7 +7,7 @@ This guide lists **breaking changes** when migrating from the original `Computer
 ## Breaking Changes

 - **Initialization:**
-  - `ComputerAgent` (v0.4.x) uses `model` as a string (e.g. "anthropic/claude-3-5-sonnet-20241022") instead of `LLM` and `AgentLoop` objects.
+  - `ComputerAgent` (v0.4.x) uses `model` as a string (e.g. "anthropic/claude-sonnet-4-5-20250929") instead of `LLM` and `AgentLoop` objects.
  - `tools` is a list (can include multiple computers and decorated functions).
  - `callbacks` are now first-class for extensibility (image retention, budget, trajectory, logging, etc).
 - **No explicit `loop` parameter:**
@@ -39,7 +39,7 @@ async with Computer() as computer:
 ```python
 async with Computer() as computer:
    agent = ComputerAgent(
-        model="anthropic/claude-3-5-sonnet-20241022",
+        model="anthropic/claude-sonnet-4-5-20250929",
        tools=[computer]
    )
    messages = [{"role": "user", "content": "Take a screenshot"}]
--- a/docs/content/docs/agent-sdk/prompt-caching.mdx
+++ b/docs/content/docs/agent-sdk/prompt-caching.mdx
@@ -38,7 +38,7 @@ With the OpenAI provider, prompt caching is handled automatically for prompts of
 ```python
 from agent import ComputerAgent
 agent = ComputerAgent(
-    model="anthropic/claude-3-5-sonnet-20241022",
+    model="anthropic/claude-sonnet-4-5-20250929",
    use_prompt_caching=True,
 )
 ```
--- a/docs/content/docs/agent-sdk/supported-agents/composed-agents.mdx
+++ b/docs/content/docs/agent-sdk/supported-agents/composed-agents.mdx
@@ -32,7 +32,7 @@ Any vision-enabled LiteLLM-compatible model can be used as the planning componen
 - Any All‑in‑one CUA (planning-capable). See [All‑in‑one CUAs](./computer-use-agents).
 - Any VLM via LiteLLM providers: `anthropic/*`, `openai/*`, `openrouter/*`, `gemini/*`, `vertex_ai/*`, `huggingface-local/*`, `mlx/*`, etc.
 - Examples:
-  - **Anthropic**: `anthropic/claude-3-5-sonnet-20241022`, `anthropic/claude-opus-4-1-20250805`
+  - **Anthropic**: `anthropic/claude-sonnet-4-5-20250929`, `anthropic/claude-opus-4-1-20250805`
  - **OpenAI**: `openai/gpt-5`, `openai/gpt-o3`, `openai/gpt-4o`
  - **Google**: `gemini/gemini-1.5-pro`, `vertex_ai/gemini-pro-vision`
  - **Local models**: Any Hugging Face vision-language model
@@ -59,7 +59,7 @@ Combine state-of-the-art grounding with powerful reasoning:

 ```python
 agent = ComputerAgent(
-    "huggingface-local/HelloKKMe/GTA1-7B+anthropic/claude-3-5-sonnet-20241022",
+    "huggingface-local/HelloKKMe/GTA1-7B+anthropic/claude-sonnet-4-5-20250929",
    tools=[computer]
 )

@@ -113,7 +113,7 @@ async for _ in agent.run("Close the settings window, then open the Downloads fol
 Composed agents support both capabilities:

 ```python
-agent = ComputerAgent("huggingface-local/HelloKKMe/GTA1-7B+anthropic/claude-3-5-sonnet-20241022")
+agent = ComputerAgent("huggingface-local/HelloKKMe/GTA1-7B+anthropic/claude-sonnet-4-5-20250929")

 # Full computer-use agent capabilities
 async for _ in agent.run("Complete this online form"):
--- a/docs/content/docs/agent-sdk/supported-agents/computer-use-agents.mdx
+++ b/docs/content/docs/agent-sdk/supported-agents/computer-use-agents.mdx
@@ -29,10 +29,9 @@ Claude models with computer-use capabilities:
 - Claude 4.1: `claude-opus-4-1-20250805`
 - Claude 4: `claude-opus-4-20250514`, `claude-sonnet-4-20250514`
 - Claude 3.7: `claude-3-7-sonnet-20250219`
- Claude 3.5: `claude-3-5-sonnet-20241022`

 ```python
-agent = ComputerAgent("claude-3-5-sonnet-20241022", tools=[computer])
+agent = ComputerAgent("claude-sonnet-4-5-20250929", tools=[computer])
 async for _ in agent.run("Open Firefox and navigate to github.com"):
    pass
 ```
--- a/docs/content/docs/agent-sdk/supported-agents/grounding-models.mdx
+++ b/docs/content/docs/agent-sdk/supported-agents/grounding-models.mdx
@@ -11,10 +11,10 @@ All models that support `ComputerAgent.run()` also support `ComputerAgent.predic

 ### Anthropic CUAs

+- Claude 4.5: `claude-sonnet-4-5-20250929`
 - Claude 4.1: `claude-opus-4-1-20250805`
 - Claude 4: `claude-opus-4-20250514`, `claude-sonnet-4-20250514`
 - Claude 3.7: `claude-3-7-sonnet-20250219`
- Claude 3.5: `claude-3-5-sonnet-20241022`

 ### OpenAI CUA Preview

@@ -61,7 +61,7 @@ Moondream3 is a powerful small model that can perform UI grounding and click pre

 ```python
 # Using any grounding model for click prediction
-agent = ComputerAgent("claude-3-5-sonnet-20241022", tools=[computer])
+agent = ComputerAgent("claude-sonnet-4-5-20250929", tools=[computer])

 # Predict coordinates for specific elements
 login_coords = agent.predict_click("find the login button")
@@ -75,7 +75,7 @@ print(f"Menu icon: {menu_coords}")

 ```python
 # OmniParser is just for OCR, so it requires an LLM for predict_click
-agent = ComputerAgent("omniparser+anthropic/claude-3-5-sonnet-20241022", tools=[computer])
+agent = ComputerAgent("omniparser+anthropic/claude-sonnet-4-5-20250929", tools=[computer])

 # Predict click coordinates using composed agent
 coords = agent.predict_click("find the submit button")
--- a/docs/content/docs/agent-sdk/supported-model-providers/index.mdx
+++ b/docs/content/docs/agent-sdk/supported-model-providers/index.mdx
@@ -28,7 +28,6 @@ model="cua/anthropic/claude-haiku-4.5"    # Claude Haiku 4.5 (faster)
 Direct access to Anthropic's Claude models using your own Anthropic API key (BYOK - Bring Your Own Key).

 ```python
-model="anthropic/claude-3-5-sonnet-20241022"
 model="anthropic/claude-3-7-sonnet-20250219"
 model="anthropic/claude-opus-4-20250514"
 model="anthropic/claude-sonnet-4-20250514"
@@ -62,6 +61,6 @@ Combine Omniparser for UI understanding with any LLM provider.
 ```python
 model="omniparser+ollama_chat/mistral-small3.2"
 model="omniparser+vertex_ai/gemini-pro"
-model="omniparser+anthropic/claude-3-5-sonnet-20241022"
+model="omniparser+anthropic/claude-sonnet-4-5-20250929"
 model="omniparser+openai/gpt-4o"
 ```
--- a/docs/content/docs/agent-sdk/telemetry.mdx
+++ b/docs/content/docs/agent-sdk/telemetry.mdx
@@ -118,7 +118,7 @@ Telemetry settings are configured at initialization and can't be changed afterwa
 | Event Name              | Data Collected                                                                                                                                                                                                                                                                                                        | Trigger Notes                                                         |
 | ----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------- |
 | **module_init**         | • `module`: "agent"<br />• `version`: Package version<br />• `python_version`: Full Python version string                                                                                                                                                                                                             | Triggered once when the agent package is imported for the first time  |
-| **agent_session_start** | • `session_id`: Unique UUID for this agent instance<br />• `agent_type`: Class name (e.g., "ComputerAgent")<br />• `model`: Model name (e.g., "claude-3-5-sonnet")<br />• `os`: Operating system<br />• `os_version`: OS version<br />• `python_version`: Python version                                              | Triggered when TelemetryCallback is initialized (agent instantiation) |
+| **agent_session_start** | • `session_id`: Unique UUID for this agent instance<br />• `agent_type`: Class name (e.g., "ComputerAgent")<br />• `model`: Model name (e.g., "claude-sonnet-4-5")<br />• `os`: Operating system<br />• `os_version`: OS version<br />• `python_version`: Python version                                              | Triggered when TelemetryCallback is initialized (agent instantiation) |
 | **agent_run_start**     | • `session_id`: Agent session UUID<br />• `run_id`: Unique UUID for this run<br />• `start_time`: Unix timestamp<br />• `input_context_size`: Character count of input messages<br />• `num_existing_messages`: Count of existing messages<br />• `uploaded_trajectory`: Full conversation items (opt-in)             | Triggered at the start of each agent.run() call                       |
 | **agent_run_end**       | • `session_id`: Agent session UUID<br />• `run_id`: Run UUID<br />• `end_time`: Unix timestamp<br />• `duration_seconds`: Total run duration<br />• `num_steps`: Total steps taken in this run<br />• `total_usage`: Accumulated token usage and costs<br />• `uploaded_trajectory`: Full conversation items (opt-in) | Triggered at the end of each agent.run() call                         |
 | **agent_step**          | • `session_id`: Agent session UUID<br />• `run_id`: Run UUID<br />• `step`: Step number (incremental)<br />• `timestamp`: Unix timestamp<br />• `duration_seconds`: Duration of previous step                                                                                                                         | Triggered on each agent response/step during a run                    |
--- a/docs/content/docs/libraries/mcp-server/configuration.mdx
+++ b/docs/content/docs/libraries/mcp-server/configuration.mdx
@@ -6,7 +6,7 @@ The server is configured using environment variables (can be set in the Claude D

 | Variable                       | Description                                                                                                                                                                                                                                       | Default                            |
 | ------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------- |
-| `CUA_MODEL_NAME`               | Model string (e.g., "anthropic/claude-sonnet-4-20250514", "anthropic/claude-3-5-sonnet-20240620", "openai/computer-use-preview", "huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B", "omniparser+litellm/gpt-4o", "omniparser+ollama_chat/gemma3") | anthropic/claude-sonnet-4-20250514 |
+| `CUA_MODEL_NAME`               | Model string (e.g., "anthropic/claude-sonnet-4-20250514", "openai/computer-use-preview", "huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B", "omniparser+litellm/gpt-4o", "omniparser+ollama_chat/gemma3") | anthropic/claude-sonnet-4-20250514 |
 | `ANTHROPIC_API_KEY`            | Your Anthropic API key (required for Anthropic models)                                                                                                                                                                                            | None                               |
 | `CUA_MAX_IMAGES`               | Maximum number of images to keep in context                                                                                                                                                                                                       | 3                                  |
 | `CUA_USE_HOST_COMPUTER_SERVER` | Target your local desktop instead of a VM. Set to "true" to use your host system. **Warning:** AI models may perform risky actions.                                                                                                               | false                              |
@@ -17,7 +17,7 @@ The `CUA_MODEL_NAME` environment variable supports various model providers throu

 ### Supported Providers

- **Anthropic**: `anthropic/claude-sonnet-4-20250514`, `anthropic/claude-3-5-sonnet-20240620`, `anthropic/claude-3-haiku-20240307`
+- **Anthropic**: `anthropic/claude-sonnet-4-20250514`, 
 - **OpenAI**: `openai/computer-use-preview`, `openai/gpt-4o`
 - **Local Models**: `huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B`
 - **Omni + LiteLLM**: `omniparser+litellm/gpt-4o`, `omniparser+litellm/claude-3-haiku`
--- a/docs/content/docs/libraries/mcp-server/installation.mdx
+++ b/docs/content/docs/libraries/mcp-server/installation.mdx
@@ -124,8 +124,6 @@ If you're working with the CUA source code directly (like in the CUA repository)

 3. **"model not found"** - Use a valid model name:
   - ✅ `anthropic/claude-sonnet-4-20250514`
-   - ✅ `anthropic/claude-3-5-sonnet-20240620`
-   - ❌ `anthropic/claude-3-5-sonnet-20241022` (doesn't exist)

 4. **Script not found** - If you get a `/bin/bash: ~/cua/libs/python/mcp-server/scripts/start_mcp_server.sh: No such file or directory` error, try changing the path to the script to be absolute instead of relative.

--- a/docs/content/docs/libraries/mcp-server/llm-integrations.mdx
+++ b/docs/content/docs/libraries/mcp-server/llm-integrations.mdx
@@ -12,7 +12,7 @@ This MCP server features comprehensive liteLLM integration, allowing you to use

 ### Model String Examples:

- **Anthropic**: `"anthropic/claude-3-5-sonnet-20241022"`
+- **Anthropic**: `"anthropic/claude-sonnet-4-5-20250929"`
 - **OpenAI**: `"openai/computer-use-preview"`
 - **UI-TARS**: `"huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B"`
 - **Omni + Any LiteLLM**: `"omniparser+litellm/gpt-4o"`, `"omniparser+litellm/claude-3-haiku"`, `"omniparser+ollama_chat/gemma3"`
--- a/docs/content/docs/libraries/mcp-server/usage.mdx
+++ b/docs/content/docs/libraries/mcp-server/usage.mdx
@@ -91,7 +91,7 @@ Add the `CUA_USE_HOST_COMPUTER_SERVER` environment variable to your MCP client c
          "command": "/bin/bash",
          "args": ["~/.cua/start_mcp_server.sh"],
          "env": {
-            "CUA_MODEL_NAME": "anthropic/claude-3-5-sonnet-20241022",
+            "CUA_MODEL_NAME": "anthropic/claude-sonnet-4-5-20250929",
            "CUA_USE_HOST_COMPUTER_SERVER": "true"
          }
        }
@@ -164,7 +164,6 @@ Now Claude will control your local desktop directly when you ask it to perform c
 **Model Selection**: Choose the appropriate model for your needs:

 - **Claude Sonnet 4**: Latest model with best performance (`anthropic/claude-sonnet-4-20250514`)
- **Claude 3.5 Sonnet**: Reliable performance (`anthropic/claude-3-5-sonnet-20240620`)
 - **Computer-Use Preview**: Specialized for computer tasks (`openai/computer-use-preview`)
 - **Local Models**: For privacy-sensitive environments
 - **Ollama**: For offline usage
--- a/libs/python/agent/README.md
+++ b/libs/python/agent/README.md
@@ -51,7 +51,7 @@ async def main():

        # Create agent
        agent = ComputerAgent(
-            model="anthropic/claude-3-5-sonnet-20241022",
+            model="anthropic/claude-sonnet-4-5-20250929",
            tools=[computer],
            only_n_most_recent_images=3,
            trajectory_dir="trajectories",
--- a/libs/python/agent/agent/agent.py
+++ b/libs/python/agent/agent/agent.py
@@ -189,7 +189,7 @@ class ComputerAgent:
        Initialize ComputerAgent.

        Args:
-            model: Model name (e.g., "claude-3-5-sonnet-20241022", "computer-use-preview", "omni+vertex_ai/gemini-pro")
+            model: Model name (e.g., "claude-sonnet-4-5-20250929", "computer-use-preview", "omni+vertex_ai/gemini-pro")
            tools: List of tools (computer objects, decorated functions, etc.)
            custom_loop: Custom agent loop function to use instead of auto-selection
            only_n_most_recent_images: If set, only keep the N most recent images in message history. Adds ImageRetentionCallback automatically.
--- a/libs/python/agent/agent/cli.py
+++ b/libs/python/agent/agent/cli.py
@@ -7,7 +7,7 @@ Usage:
 Examples:
    python -m agent.cli openai/computer-use-preview
    python -m agent.cli anthropic/claude-sonnet-4-5-20250929
-    python -m agent.cli omniparser+anthropic/claude-3-5-sonnet-20241022
+    python -m agent.cli omniparser+anthropic/claude-sonnet-4-5-20250929
 """

 try:
@@ -233,7 +233,7 @@ async def main():
 Examples:
  python -m agent.cli openai/computer-use-preview
  python -m agent.cli anthropic/claude-sonnet-4-5-20250929
-  python -m agent.cli omniparser+anthropic/claude-3-5-sonnet-20241022
+  python -m agent.cli omniparser+anthropic/claude-sonnet-4-5-20250929
  python -m agent.cli huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B
        """,
    )
--- a/libs/python/agent/agent/proxy/examples.py
+++ b/libs/python/agent/agent/proxy/examples.py
@@ -22,14 +22,14 @@ async def test_http_endpoint():

    # Example 1: Simple text request
    simple_request = {
-        "model": "anthropic/claude-3-5-sonnet-20241022",
+        "model": "anthropic/claude-sonnet-4-5-20250929",
        "input": "Tell me a three sentence bedtime story about a unicorn.",
        "env": {"ANTHROPIC_API_KEY": anthropic_api_key},
    }

    # Example 2: Multi-modal request with image
    multimodal_request = {
-        "model": "anthropic/claude-3-5-sonnet-20241022",
+        "model": "anthropic/claude-sonnet-4-5-20250929",
        "input": [
            {
                "role": "user",
@@ -47,7 +47,7 @@ async def test_http_endpoint():

    # Example 3: Request with custom agent and computer kwargs
    custom_request = {
-        "model": "anthropic/claude-3-5-sonnet-20241022",
+        "model": "anthropic/claude-sonnet-4-5-20250929",
        "input": "Take a screenshot and tell me what you see",
        "env": {"ANTHROPIC_API_KEY": anthropic_api_key},
    }
@@ -95,7 +95,7 @@ def curl_examples():
        """curl http://localhost:8000/responses \\
  -H "Content-Type: application/json" \\
  -d '{
-    "model": "anthropic/claude-3-5-sonnet-20241022",
+    "model": "anthropic/claude-sonnet-4-5-20250929",
    "input": "Tell me a three sentence bedtime story about a unicorn."
  }'"""
    )
@@ -105,7 +105,7 @@ def curl_examples():
        """curl http://localhost:8000/responses \\
  -H "Content-Type: application/json" \\
  -d '{
-    "model": "anthropic/claude-3-5-sonnet-20241022",
+    "model": "anthropic/claude-sonnet-4-5-20250929",
    "input": [
      {
        "role": "user",
@@ -126,7 +126,7 @@ def curl_examples():
        """curl http://localhost:8000/responses \\
  -H "Content-Type: application/json" \\
  -d '{
-    "model": "anthropic/claude-3-5-sonnet-20241022",
+    "model": "anthropic/claude-sonnet-4-5-20250929",
    "input": "Take a screenshot and tell me what you see",
    "agent_kwargs": {
      "save_trajectory": true,
@@ -166,7 +166,7 @@ async def test_p2p_client():

            # Send a test request
            request = {
-                "model": "anthropic/claude-3-5-sonnet-20241022",
+                "model": "anthropic/claude-sonnet-4-5-20250929",
                "input": "Hello from P2P client!",
            }
            await connection.send(json.dumps(request))
--- a/libs/python/agent/agent/ui/gradio/app.py
+++ b/libs/python/agent/agent/ui/gradio/app.py
@@ -6,9 +6,9 @@ with an advanced UI for model selection and configuration.

 Supported Agent Models:
 - OpenAI: openai/computer-use-preview
- Anthropic: anthropic/claude-3-5-sonnet-20241022, anthropic/claude-3-7-sonnet-20250219
+- Anthropic: anthropic/claude-sonnet-4-5-20250929, anthropic/claude-3-7-sonnet-20250219
 - UI-TARS: huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B
- Omniparser: omniparser+anthropic/claude-3-5-sonnet-20241022, omniparser+ollama_chat/gemma3
+- Omniparser: omniparser+anthropic/claude-sonnet-4-5-20250929, omniparser+ollama_chat/gemma3

 Requirements:
    - Mac with Apple Silicon (M1/M2/M3/M4), Linux, or Windows
@@ -116,14 +116,12 @@ MODEL_MAPPINGS = {
        "Anthropic: Claude 4 Opus (20250514)": "anthropic/claude-opus-4-20250514",
        "Anthropic: Claude 4 Sonnet (20250514)": "anthropic/claude-sonnet-4-20250514",
        "Anthropic: Claude 3.7 Sonnet (20250219)": "anthropic/claude-3-7-sonnet-20250219",
-        "Anthropic: Claude 3.5 Sonnet (20241022)": "anthropic/claude-3-5-sonnet-20241022",
    },
    "omni": {
        "default": "omniparser+openai/gpt-4o",
        "OMNI: OpenAI GPT-4o": "omniparser+openai/gpt-4o",
        "OMNI: OpenAI GPT-4o mini": "omniparser+openai/gpt-4o-mini",
        "OMNI: Claude 3.7 Sonnet (20250219)": "omniparser+anthropic/claude-3-7-sonnet-20250219",
-        "OMNI: Claude 3.5 Sonnet (20241022)": "omniparser+anthropic/claude-3-5-sonnet-20241022",
    },
    "uitars": {
        "default": "huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B" if is_mac else "ui-tars",
--- a/libs/python/agent/agent/ui/gradio/ui_components.py
+++ b/libs/python/agent/agent/ui/gradio/ui_components.py
@@ -44,13 +44,11 @@ def create_gradio_ui() -> gr.Blocks:
        "Anthropic: Claude 4 Opus (20250514)",
        "Anthropic: Claude 4 Sonnet (20250514)",
        "Anthropic: Claude 3.7 Sonnet (20250219)",
-        "Anthropic: Claude 3.5 Sonnet (20241022)",
    ]
    omni_models = [
        "OMNI: OpenAI GPT-4o",
        "OMNI: OpenAI GPT-4o mini",
        "OMNI: Claude 3.7 Sonnet (20250219)",
-        "OMNI: Claude 3.5 Sonnet (20241022)",
    ]

    # Check if API keys are available
--- a/libs/python/agent/example.py
+++ b/libs/python/agent/example.py
@@ -102,7 +102,7 @@ async def main():
            # model="anthropic/claude-opus-4-20250514",
            # model="anthropic/claude-sonnet-4-20250514",
            # model="anthropic/claude-3-7-sonnet-20250219",
-            # model="anthropic/claude-3-5-sonnet-20241022",
+            # model="anthropic/claude-sonnet-4-5-20250929",
            # == UI-TARS ==
            # model="huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B",
            # TODO: add local mlx provider
--- a/libs/python/agent/tests/conftest.py
+++ b/libs/python/agent/tests/conftest.py
@@ -24,7 +24,7 @@ def mock_litellm():
                "id": "chatcmpl-test123",
                "object": "chat.completion",
                "created": 1234567890,
-                "model": kwargs.get("model", "anthropic/claude-3-5-sonnet-20241022"),
+                "model": kwargs.get("model", "anthropic/claude-sonnet-4-5-20250929"),
                "choices": [
                    {
                        "index": 0,
--- a/libs/python/agent/tests/test_computer_agent.py
+++ b/libs/python/agent/tests/test_computer_agent.py
@@ -18,18 +18,18 @@ class TestComputerAgentInitialization:
        """Test that agent can be initialized with a model string."""
        from agent import ComputerAgent

-        agent = ComputerAgent(model="anthropic/claude-3-5-sonnet-20241022")
+        agent = ComputerAgent(model="anthropic/claude-sonnet-4-5-20250929")

        assert agent is not None
        assert hasattr(agent, "model")
-        assert agent.model == "anthropic/claude-3-5-sonnet-20241022"
+        assert agent.model == "anthropic/claude-sonnet-4-5-20250929"

    @patch("agent.agent.litellm")
    def test_agent_initialization_with_tools(self, mock_litellm, disable_telemetry, mock_computer):
        """Test that agent can be initialized with tools."""
        from agent import ComputerAgent

-        agent = ComputerAgent(model="anthropic/claude-3-5-sonnet-20241022", tools=[mock_computer])
+        agent = ComputerAgent(model="anthropic/claude-sonnet-4-5-20250929", tools=[mock_computer])

        assert agent is not None
        assert hasattr(agent, "tools")
@@ -41,7 +41,7 @@ class TestComputerAgentInitialization:

        budget = 5.0
        agent = ComputerAgent(
-            model="anthropic/claude-3-5-sonnet-20241022", max_trajectory_budget=budget
+            model="anthropic/claude-sonnet-4-5-20250929", max_trajectory_budget=budget
        )

        assert agent is not None
@@ -79,7 +79,7 @@ class TestComputerAgentRun:

        mock_litellm.acompletion = AsyncMock(return_value=mock_response)

-        agent = ComputerAgent(model="anthropic/claude-3-5-sonnet-20241022")
+        agent = ComputerAgent(model="anthropic/claude-sonnet-4-5-20250929")

        # Run should return an async generator
        result_generator = agent.run(sample_messages)
@@ -92,7 +92,7 @@ class TestComputerAgentRun:
        """Test that agent has run method available."""
        from agent import ComputerAgent

-        agent = ComputerAgent(model="anthropic/claude-3-5-sonnet-20241022")
+        agent = ComputerAgent(model="anthropic/claude-sonnet-4-5-20250929")

        # Verify run method exists
        assert hasattr(agent, "run")
@@ -102,7 +102,7 @@ class TestComputerAgentRun:
        """Test that agent has agent_loop initialized."""
        from agent import ComputerAgent

-        agent = ComputerAgent(model="anthropic/claude-3-5-sonnet-20241022")
+        agent = ComputerAgent(model="anthropic/claude-sonnet-4-5-20250929")

        # Verify agent_loop is initialized
        assert hasattr(agent, "agent_loop")
@@ -132,7 +132,7 @@ class TestComputerAgentIntegration:
        """Test that agent can be initialized with Computer tool."""
        from agent import ComputerAgent

-        agent = ComputerAgent(model="anthropic/claude-3-5-sonnet-20241022", tools=[mock_computer])
+        agent = ComputerAgent(model="anthropic/claude-sonnet-4-5-20250929", tools=[mock_computer])

        # Verify agent accepted the tool
        assert agent is not None
--- a/libs/python/mcp-server/CONCURRENT_SESSIONS.md
+++ b/libs/python/mcp-server/CONCURRENT_SESSIONS.md
@@ -133,7 +133,7 @@ await cleanup_session(ctx, "session-to-cleanup")

 ### Environment Variables

- `CUA_MODEL_NAME`: Model to use (default: `anthropic/claude-3-5-sonnet-20241022`)
+- `CUA_MODEL_NAME`: Model to use (default: `anthropic/claude-sonnet-4-5-20250929`)
 - `CUA_MAX_IMAGES`: Maximum images to keep (default: `3`)

 ### Session Manager Configuration
--- a/libs/python/mcp-server/README.md
+++ b/libs/python/mcp-server/README.md
@@ -44,7 +44,7 @@ Add this to your MCP client configuration:
      "args": [
        "bash",
        "-lc",
-        "export CUA_MODEL_NAME='anthropic/claude-3-5-sonnet-20241022'; ~/.cua/start_mcp_server.sh"
+        "export CUA_MODEL_NAME='anthropic/claude-sonnet-4-5-20250929'; ~/.cua/start_mcp_server.sh"
      ]
    }
  }
--- a/libs/python/mcp-server/mcp_server/server.py
+++ b/libs/python/mcp-server/mcp_server/server.py
@@ -156,7 +156,7 @@ def serve() -> FastMCP:

                try:
                    # Get model name
-                    model_name = os.getenv("CUA_MODEL_NAME", "anthropic/claude-3-5-sonnet-20241022")
+                    model_name = os.getenv("CUA_MODEL_NAME", "anthropic/claude-sonnet-4-5-20250929")
                    logger.info(f"Using model: {model_name}")

                    # Create agent with the new v0.4.x API
--- a/libs/python/mcp-server/quick_test_local_option.py
+++ b/libs/python/mcp-server/quick_test_local_option.py
@@ -168,7 +168,7 @@ def print_usage_examples():
      "command": "/bin/bash",
      "args": ["~/.cua/start_mcp_server.sh"],
      "env": {
-        "CUA_MODEL_NAME": "anthropic/claude-3-5-sonnet-20241022"
+        "CUA_MODEL_NAME": "anthropic/claude-sonnet-4-5-20250929"
      }
    }
  }
@@ -192,7 +192,7 @@ Step 2: Configure MCP client:
      "command": "/bin/bash",
      "args": ["~/.cua/start_mcp_server.sh"],
      "env": {
-        "CUA_MODEL_NAME": "anthropic/claude-3-5-sonnet-20241022",
+        "CUA_MODEL_NAME": "anthropic/claude-sonnet-4-5-20250929",
        "CUA_USE_HOST_COMPUTER_SERVER": "true"
      }
    }
--- a/libs/typescript/agent/README.md
+++ b/libs/typescript/agent/README.md
@@ -32,7 +32,7 @@ const peerClient = new AgentClient('peer://my-agent-proxy');

 // Send a simple text request
 const response = await client.responses.create({
-  model: 'anthropic/claude-3-5-sonnet-20241022',
+  model: 'anthropic/claude-sonnet-4-5-20250929',
  input: 'Write a one-sentence bedtime story about a unicorn.',
  // Optional per-request env overrides
  env: {
@@ -47,7 +47,7 @@ console.log(response.output);

 ```typescript
 const response = await client.responses.create({
-  model: 'anthropic/claude-3-5-sonnet-20241022',
+  model: 'anthropic/claude-sonnet-4-5-20250929',
  input: [
    {
      role: 'user',
@@ -74,7 +74,7 @@ const client = new AgentClient('https://localhost:8000', {
 });

 const response = await client.responses.create({
-  model: 'anthropic/claude-3-5-sonnet-20241022',
+  model: 'anthropic/claude-sonnet-4-5-20250929',
  input: 'Hello, world!',
  agent_kwargs: {
    save_trajectory: true,
--- a/libs/typescript/agent/examples/README.md
+++ b/libs/typescript/agent/examples/README.md
@@ -42,7 +42,7 @@ A simple HTML page that demonstrates using the CUA Agent Client in a browser env

 4. **Configure and test:**
   - Enter an agent URL (e.g., `https://localhost:8000` or `peer://some-peer-id`)
-   - Enter a model name (e.g., `anthropic/claude-3-5-sonnet-20241022`)
+   - Enter a model name (e.g., `anthropic/claude-sonnet-4-5-20250929`)
   - Type a message and click "Send Message" or press Enter
   - View the response in the output textarea

@@ -53,7 +53,7 @@ A simple HTML page that demonstrates using the CUA Agent Client in a browser env

 **Example Models:**

- `anthropic/claude-3-5-sonnet-20241022`
+- `anthropic/claude-sonnet-4-5-20250929`
 - `openai/gpt-4`
 - `huggingface-local/microsoft/UI-TARS-7B`

--- a/notebooks/ollama_nb.ipynb
+++ b/notebooks/ollama_nb.ipynb
@@ -203,7 +203,7 @@
    "\n",
    "Examples:\n",
    "- `openai/computer-use-preview+ollama/gemma3:4b`\n",
-    "- `anthropic/claude-3-5-sonnet-20241022+ollama/gemma3:4b`\n"
+    "- `anthropic/claude-sonnet-4-5-20250929+ollama/gemma3:4b`\n"
   ]
  },
  {
@@ -217,7 +217,7 @@
    "import logging\n",
    "\n",
    "agent_composed = ComputerAgent(\n",
-    "    model=\"anthropic/claude-3-5-sonnet-20241022+ollama/gemma3:4b\",\n",
+    "    model=\"anthropic/claude-sonnet-4-5-20250929+ollama/gemma3:4b\",\n",
    "    tools=[computer],\n",
    "    trajectory_dir=\"trajectories\",\n",
    "    only_n_most_recent_images=3,\n",
@@ -234,7 +234,20 @@
   "cell_type": "markdown",
   "id": "section-3-conceptual",
   "metadata": {},
-   "source": "## 3) Customize your agent 🛠️\n\nFor a few customization options, see: https://cua.ai/docs/agent-sdk/customizing-computeragent\n\nLevels of customization you can explore:\n\n1) Simple — Prompt engineering\n2) Easy — Tools\n3) Intermediate — Callbacks\n4) Expert — Custom agent via `register_agent` (see `libs/python/agent/agent/decorators.py` → `register_agent`)\n\nor, incorporate the ComputerAgent into your own agent framework!"
+   "source": [
+    "## 3) Customize your agent 🛠️\n",
+    "\n",
+    "For a few customization options, see: https://cua.ai/docs/agent-sdk/customizing-computeragent\n",
+    "\n",
+    "Levels of customization you can explore:\n",
+    "\n",
+    "1) Simple — Prompt engineering\n",
+    "2) Easy — Tools\n",
+    "3) Intermediate — Callbacks\n",
+    "4) Expert — Custom agent via `register_agent` (see `libs/python/agent/agent/decorators.py` → `register_agent`)\n",
+    "\n",
+    "or, incorporate the ComputerAgent into your own agent framework!"
+   ]
  },
  {
   "cell_type": "markdown",
@@ -274,4 +287,4 @@
 },
 "nbformat": 4,
 "nbformat_minor": 5
-}
+}
--- a/tests/agent_loop_testing/agent_test.py
+++ b/tests/agent_loop_testing/agent_test.py
@@ -184,7 +184,7 @@ if __name__ == "__main__":

    parser = argparse.ArgumentParser(description="Test CUA Agent with mock computer")
    parser.add_argument(
-        "--model", default="anthropic/claude-sonnet-4-20250514", help="CUA model to test"
+        "--model", default="anthropic/claude-sonnet-4-5-20250929", help="CUA model to test"
    )
    args = parser.parse_args()