scriptoriumadmin/litellm
1
0
Fork 0
mirror of https://github.com/BerriAI/litellm.git synced 2026-10-09 03:18:44 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 109

fix: correct context window tokens for GPT-5 Pro and GPT-5.4 Mini/Nano

Browse source 
Three bugs in model_prices_and_context_window.json:

1. gpt-5-pro and gpt-5-pro-2025-10-06: max_input_tokens and max_tokens
   were SWAPPED. GPT-5 Pro has a 400K context window (input) with 128K
   max output, but the values were set as max_input=128000,
   max_tokens=272000. This caused token limit errors when sending
   prompts over 128K tokens to GPT-5 Pro.

2. gpt-5.4-mini and gpt-5.4-mini-2026-03-17: max_input_tokens was
   272000, but GPT-5.4 Mini shares the same 1,050,000 token context
   window as GPT-5.4. This was inconsistent with the azure/ variants
   which already correctly had 1,050,000.

3. gpt-5.4-nano and gpt-5.4-nano-2026-03-17: same issue as Mini,
   max_input_tokens was 272000 instead of 1,050,000.

Source: OpenAI model documentation and contextwindows.dev which
aggregates official context window sizes.

Fixes #30928 (partially — the issue incorrectly claims gpt-5/gpt-5-mini
should be 400K; their 272K values are correct per OpenAI docs)
This commit is contained in:
xbrxr03 2026-06-21 20:09:45 -04:00
parent 3818d6401c
commit 15462f7d1d
1 changed files with 8 additions and 8 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

16
model_prices_and_context_window.json
View file

@ -22388,7 +22388,7 @@
"input_cost_per_token_batches": 3.75e-07,
"input_cost_per_token_priority": 1.5e-06,
"litellm_provider": "openai",
"max_input_tokens": 272000,
"max_input_tokens": 1050000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
@ -22436,7 +22436,7 @@
"input_cost_per_token_batches": 3.75e-07,
"input_cost_per_token_priority": 1.5e-06,
"litellm_provider": "openai",
"max_input_tokens": 272000,
"max_input_tokens": 1050000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
@ -22482,7 +22482,7 @@
"input_cost_per_token_flex": 1e-07,
"input_cost_per_token_batches": 1e-07,
"litellm_provider": "openai",
"max_input_tokens": 272000,
"max_input_tokens": 1050000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
@ -22527,7 +22527,7 @@
"input_cost_per_token_flex": 1e-07,
"input_cost_per_token_batches": 1e-07,
"litellm_provider": "openai",
"max_input_tokens": 272000,
"max_input_tokens": 1050000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
@ -22568,9 +22568,9 @@
"input_cost_per_token": 1.5e-05,
"input_cost_per_token_batches": 7.5e-06,
"litellm_provider": "openai",
"max_input_tokens": 128000,
"max_input_tokens": 400000,
"max_output_tokens": 272000,
"max_tokens": 272000,
"max_tokens": 128000,
"mode": "responses",
"output_cost_per_token": 0.00012,
"output_cost_per_token_batches": 6e-05,
@ -22604,9 +22604,9 @@
"input_cost_per_token": 1.5e-05,
"input_cost_per_token_batches": 7.5e-06,
"litellm_provider": "openai",
"max_input_tokens": 128000,
"max_input_tokens": 400000,
"max_output_tokens": 272000,
"max_tokens": 272000,
"max_tokens": 128000,
"mode": "responses",
"output_cost_per_token": 0.00012,
"output_cost_per_token_batches": 6e-05,