surshar / claude-code
Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.
Built by Anthropic · github.com/anthropics
Fast Opus 4.5 Model Configuration
Issue
The standard Opus 4.5 configuration is limited to 200,000 tokens, causing failures with larger contexts.
Solution: Fast Opus Deployment
Environment Variable Configuration
To use the fast Opus deployment with extended context length, configure Claude Code with:
# Set the Opus alias to use the fast deployment
export ANTHROPIC_DEFAULT_OPUS_MODEL="claude-opus-4-5-20251101-fast"
Model String Updates for Fast Deployment
| Platform | Fast Opus 4.5 Model String |
|---|---|
| Anthropic API (1P) | claude-opus-4-5-20251101-fast |
| AWS Bedrock | anthropic.claude-opus-4-5-20251101-fast-v1:0 |
| Google Vertex AI | claude-opus-4-5-fast@20251101 |
| Azure AI Foundry | claude-opus-4-5-20251101-fast |
Context Length Configuration
The fast deployment supports extended context. Configure the context limit:
# Extended context configuration (up to 1M tokens)
export ANTHROPIC_OPUS_CONTEXT_LIMIT="1000000"
Integration with Migration Tool
When migrating to Opus 4.5 with extended context requirements:
- Use the fast model strings above instead of standard ones
- Set the environment variable for Opus alias
- Configure extended context limit
- Test with large contexts (>200k tokens)
VSCode Configuration
For VSCode extension users:
{
"claude-code.environmentVariables": {
"ANTHROPIC_DEFAULT_OPUS_MODEL": "claude-opus-4-5-20251101-fast",
"ANTHROPIC_OPUS_CONTEXT_LIMIT": "1000000"
}
}
Verification
Test the configuration with a prompt that exceeds 200k tokens to ensure the error:
prompt is too long: 282789 tokens > 200000 maximum
is resolved.
When to Use Fast vs Standard
- Use Fast: For large codebases, extensive context analysis, long conversations
- Use Standard: For typical development tasks with smaller context requirements
The fast deployment trades some response speed for much higher context capacity.