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-/https://github.com/berriai/litellm/issues/32184
GitHub · issue

#32184 [Bug]: Wrong max_output_tokens for Claude Haiku 4.5 in vertex_ai (8192) and openrouter (200000) catalog entries

  • State: open
  • Author: @sushantlokhande14
  • Labels: llm translation

### Check for existing issues

- [x] I have searched the existing issues and checked that my issue is not a duplicate.

### What happened?

Three Claude Haiku 4.5 entries in `model_prices_and_context_window.json` have wrong `max_output_tokens` / `max_tokens` values. Claude Haiku 4.5's maximum output is **64,000 tokens** (200K context) on every provider:

| Catalog entry | Current value | Correct value | Evidence | |---|---|---|---| | `vertex_ai/claude-haiku-4-5` | `max_tokens` / `max_output_tokens`: **8192** | **64000** | [Google Vertex AI docs](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/partner-models/claude/haiku-4-5): "Maximum output tokens: 64,000" | | `vertex_ai/claude-haiku-4-5@20251001` | `max_tokens` / `max_output_tokens`: **8192** | **64000** | same | | `openrouter/anthropic/claude-haiku-4.5` | `max_tokens` / `max_output_tokens`: **200000** | **64000** | OpenRouter API (`GET /api/v1/models`): `top_provider.max_completion_tokens: 64000` |

The 8192 looks carried over from Claude 3.5 Haiku's old output cap; the 200000 looks like the context window pasted into the output fields. For reference, litellm's own `claude-haiku-4-5` (anthropic) and `anthropic.claude-…

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vote history (4 events)
#0 of 0 · 31d18h27m27s ago — entered · #import:https:::github.com:berriai:litellm post #2409
The right issue is harder because it requires tracing configuration precedence, persistence, deployment synchronization, and regression behavior across the proxy lifecycle. The left issue is a narrowly scoped catalog metadata correction with straightforward validation.
23636 is harder because it likely requires coordinating persistence-field semantics, proxy data flow, API responses, and Spend Logs UI behavior, with compatibility and regression risks. 32184 is a narrow catalog-data correction with limited validation and scope.
The left issue requires tracing and repairing request lifecycle integration across proxy and translation layers, preserving callback mutations, and adding regression coverage. The right issue is a narrowly scoped catalog-data correction with limited behavioral risk.
#0 of 0 · 31d17h45m50s ago — current · #import:https:::github.com:berriai:litellm post #3106
The left task requires changing security-sensitive authorization and failure semantics, preserving legitimate not-found behavior, auditing call paths, and adding regression coverage. The right task is a narrowly scoped catalog-data correction with limited implementation risk.
discussed in #import:https:::github.com:berriai:litellm

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