From d21e90f6831eebde5eb8f8d42604f5b57116d05e Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Fri, 24 Apr 2026 14:10:42 -0700 Subject: [PATCH] [Feat] Day-0 support for GPT-5.5 and GPT-5.5 Pro (#26449) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * feat(openai): day-0 support for GPT-5.5 and GPT-5.5 Pro Add pricing + capability entries for the new GPT-5.5 family launched by OpenAI on 2026-04-24: - gpt-5.5 / gpt-5.5-2026-04-23 (chat): $5/$30/$0.50 per 1M input/output/cached input - gpt-5.5-pro / gpt-5.5-pro-2026-04-23 (responses-only): $60/$360/$6 per 1M input/output/cached input Other fees (long-context >272k, flex, batches, priority, cache discounts) follow the same ratios as GPT-5.4, with context window retained at 1.05M input / 128K output. No transformation / classifier code changes are required: OpenAIGPT5Config.is_model_gpt_5_4_plus_model() already matches 5.5+ via numeric version parsing, and model registration is driven from the JSON. The existing responses-API bridge for tools + reasoning_effort (litellm/main.py:970) already covers gpt-5.5-pro. Tests: - GPT5_MODELS regression list now covers gpt-5.5-pro and dated variants - New test_generic_cost_per_token_gpt55_pro cost-calc test - Updated test_generic_cost_per_token_gpt55 for long-context fields * fix(openai): mirror reasoning_effort flags onto gpt-5.5 dated variants gpt-5.5-2026-04-23 and gpt-5.5-pro-2026-04-23 were missing the supports_none_reasoning_effort, supports_xhigh_reasoning_effort, and supports_minimal_reasoning_effort flags that their non-dated counterparts define. Reasoning-effort routing in OpenAIGPT5Config is fully capability-driven from these JSON flags — since an absent flag is treated as False for opt-in levels (xhigh), users pinning to a dated snapshot would silently lose xhigh support and diverge from the base alias on logprobs + flexible temperature handling. Copy the flags onto both dated variants so every dated snapshot inherits the base model's reasoning-effort capability profile. Adds a parametrized regression test that asserts supports_{none,minimal,xhigh}_reasoning_effort parity between each dated variant and its non-dated counterpart, preventing future drift when new snapshots are added. --- ...odel_prices_and_context_window_backup.json | 148 +++++++++++++++++- model_prices_and_context_window.json | 148 +++++++++++++++++- .../llm_cost_calc/test_llm_cost_calc_utils.py | 86 +++++++++- .../llms/openai/test_is_model_gpt_5_model.py | 3 + 4 files changed, 382 insertions(+), 3 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 1cf7c1f6c7..49ce5022c5 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -19275,13 +19275,24 @@ }, "gpt-5.5": { "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_flex": 2.5e-07, + "cache_read_input_token_cost_priority": 1e-06, "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_flex": 2.5e-06, + "input_cost_per_token_batches": 2.5e-06, + "input_cost_per_token_priority": 1e-05, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 1050000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_flex": 1.5e-05, + "output_cost_per_token_batches": 1.5e-05, + "output_cost_per_token_priority": 6e-05, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -19305,10 +19316,145 @@ "supports_tool_choice": true, "supports_service_tier": true, "supports_vision": true, + "supports_web_search": true, "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, + "gpt-5.5-2026-04-23": { + "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_flex": 2.5e-07, + "cache_read_input_token_cost_priority": 1e-06, + "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_flex": 2.5e-06, + "input_cost_per_token_batches": 2.5e-06, + "input_cost_per_token_priority": 1e-05, + "litellm_provider": "openai", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_flex": 1.5e-05, + "output_cost_per_token_batches": 1.5e-05, + "output_cost_per_token_priority": 6e-05, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true + }, + "gpt-5.5-pro": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "input_cost_per_token_flex": 3e-05, + "input_cost_per_token_batches": 3e-05, + "litellm_provider": "openai", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "output_cost_per_token_flex": 0.00018, + "output_cost_per_token_batches": 0.00018, + "supported_endpoints": [ + "/v1/responses", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": false, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true + }, + "gpt-5.5-pro-2026-04-23": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "input_cost_per_token_flex": 3e-05, + "input_cost_per_token_batches": 3e-05, + "litellm_provider": "openai", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "output_cost_per_token_flex": 0.00018, + "output_cost_per_token_batches": 0.00018, + "supported_endpoints": [ + "/v1/responses", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": false, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true + }, "gpt-5.4": { "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 8dcd52cae2..3733f07a30 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -19289,13 +19289,24 @@ }, "gpt-5.5": { "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_flex": 2.5e-07, + "cache_read_input_token_cost_priority": 1e-06, "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_flex": 2.5e-06, + "input_cost_per_token_batches": 2.5e-06, + "input_cost_per_token_priority": 1e-05, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 1050000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_flex": 1.5e-05, + "output_cost_per_token_batches": 1.5e-05, + "output_cost_per_token_priority": 6e-05, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -19319,10 +19330,145 @@ "supports_tool_choice": true, "supports_service_tier": true, "supports_vision": true, + "supports_web_search": true, "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, + "gpt-5.5-2026-04-23": { + "cache_read_input_token_cost": 5e-07, + "cache_read_input_token_cost_above_272k_tokens": 1e-06, + "cache_read_input_token_cost_flex": 2.5e-07, + "cache_read_input_token_cost_priority": 1e-06, + "input_cost_per_token": 5e-06, + "input_cost_per_token_above_272k_tokens": 1e-05, + "input_cost_per_token_flex": 2.5e-06, + "input_cost_per_token_batches": 2.5e-06, + "input_cost_per_token_priority": 1e-05, + "litellm_provider": "openai", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, + "output_cost_per_token_flex": 1.5e-05, + "output_cost_per_token_batches": 1.5e-05, + "output_cost_per_token_priority": 6e-05, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true + }, + "gpt-5.5-pro": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "input_cost_per_token_flex": 3e-05, + "input_cost_per_token_batches": 3e-05, + "litellm_provider": "openai", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "output_cost_per_token_flex": 0.00018, + "output_cost_per_token_batches": 0.00018, + "supported_endpoints": [ + "/v1/responses", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": false, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true + }, + "gpt-5.5-pro-2026-04-23": { + "cache_read_input_token_cost": 6e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-05, + "input_cost_per_token": 6e-05, + "input_cost_per_token_above_272k_tokens": 0.00012, + "input_cost_per_token_flex": 3e-05, + "input_cost_per_token_batches": 3e-05, + "litellm_provider": "openai", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 0.00036, + "output_cost_per_token_above_272k_tokens": 0.00054, + "output_cost_per_token_flex": 0.00018, + "output_cost_per_token_batches": 0.00018, + "supported_endpoints": [ + "/v1/responses", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_service_tier": true, + "supports_vision": true, + "supports_web_search": true, + "supports_none_reasoning_effort": false, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true + }, "gpt-5.4": { "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py index 7144279ad0..5e37e2a342 100644 --- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py +++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py @@ -343,7 +343,10 @@ def test_generic_cost_per_token_gpt55(): assert model_cost_map["cache_read_input_token_cost"] == 5e-7 assert model_cost_map["litellm_provider"] == "openai" assert model_cost_map["mode"] == "chat" - assert model_cost_map["max_input_tokens"] == 272000 + # gpt-5.5 inherits GPT-5.4's long-context window + tiered pricing. + assert model_cost_map["max_input_tokens"] == 1050000 + assert model_cost_map["input_cost_per_token_above_272k_tokens"] == 1e-5 + assert model_cost_map["output_cost_per_token_above_272k_tokens"] == 4.5e-5 prompt_tokens = 1000 completion_tokens = 500 @@ -365,6 +368,87 @@ def test_generic_cost_per_token_gpt55(): ) +def test_generic_cost_per_token_gpt55_pro(): + """gpt-5.5-pro: responses-only model — $60/1M input, $360/1M output, $6/1M cached input.""" + model = "gpt-5.5-pro" + custom_llm_provider = "openai" + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + + model_cost_map = litellm.model_cost[model] + + # Sanity-check the map values match OpenAI's published pricing. + assert model_cost_map["input_cost_per_token"] == 6e-5 + assert model_cost_map["output_cost_per_token"] == 3.6e-4 + assert model_cost_map["cache_read_input_token_cost"] == 6e-6 + assert model_cost_map["litellm_provider"] == "openai" + # gpt-5.5-pro is a responses-only model (no /v1/chat/completions endpoint). + assert model_cost_map["mode"] == "responses" + assert "/v1/chat/completions" not in model_cost_map["supported_endpoints"] + assert "/v1/responses" in model_cost_map["supported_endpoints"] + # Inherits GPT-5.4-pro's long-context window + tiered pricing (scaled 2x). + assert model_cost_map["max_input_tokens"] == 1050000 + assert model_cost_map["input_cost_per_token_above_272k_tokens"] == 1.2e-4 + assert model_cost_map["output_cost_per_token_above_272k_tokens"] == 5.4e-4 + + prompt_tokens = 1000 + completion_tokens = 500 + usage = Usage( + prompt_tokens=prompt_tokens, + completion_tokens=completion_tokens, + total_tokens=prompt_tokens + completion_tokens, + ) + prompt_cost, completion_cost = generic_cost_per_token( + model=model, + usage=usage, + custom_llm_provider=custom_llm_provider, + ) + assert round(prompt_cost, 10) == round( + model_cost_map["input_cost_per_token"] * prompt_tokens, 10 + ) + assert round(completion_cost, 10) == round( + model_cost_map["output_cost_per_token"] * completion_tokens, 10 + ) + + +@pytest.mark.parametrize( + "base_model,dated_model", + [ + ("gpt-5.5", "gpt-5.5-2026-04-23"), + ("gpt-5.5-pro", "gpt-5.5-pro-2026-04-23"), + ], +) +def test_gpt55_dated_variants_match_base_reasoning_effort_capabilities( + base_model, dated_model +): + """Dated snapshots must carry the same reasoning_effort capability flags as + their non-dated counterparts. + + Regression guard: ``supports_{none,minimal,xhigh}_reasoning_effort`` gate + downstream routing in ``OpenAIGPT5Config`` — a missing flag is treated as + ``False`` for opt-in levels (e.g. ``xhigh``), which silently diverges + behavior between ``gpt-5.5`` and ``gpt-5.5-2026-04-23``. Pinning to a + dated variant must never lose capabilities relative to the base alias. + """ + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + + base = litellm.model_cost[base_model] + dated = litellm.model_cost[dated_model] + + for flag in ( + "supports_none_reasoning_effort", + "supports_minimal_reasoning_effort", + "supports_xhigh_reasoning_effort", + ): + assert dated.get(flag) == base.get(flag), ( + f"{dated_model} has {flag}={dated.get(flag)!r}, " + f"but {base_model} has {flag}={base.get(flag)!r}. " + f"Dated snapshots must inherit the base model's reasoning_effort " + f"capability profile." + ) + + def test_generic_cost_per_token_anthropic_prompt_caching(): model = "claude-sonnet-4@20250514" usage = Usage( diff --git a/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py b/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py index e611d5e6b7..02dd9dade0 100644 --- a/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py +++ b/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py @@ -47,6 +47,9 @@ GPT5_MODELS = [ "gpt-5.3", "gpt-5.4", "gpt-5.5", + "gpt-5.5-pro", + "gpt-5.5-2026-04-23", # dated variant + "gpt-5.5-pro-2026-04-23", # dated variant "gpt-5.1-chat", # versioned chat — THE KEY REGRESSION CASE "gpt-5.2-chat", # versioned chat — also a regression case "gpt-5.3-chat", # versioned chat — THE KEY REGRESSION CASE