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Merge pull request #39417 from BerriAI/litellm_muse_spark_1_3
feat(model_prices): add meta/muse-spark-1.3 and its contributor tier
This commit is contained in:
Mateo Wang
GitHub
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2d3e4d6eff
3 changed files with 271 additions and 0 deletions
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@ -33093,6 +33093,88 @@
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"supports_web_search": true,
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"supports_xhigh_reasoning_effort": true
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},
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"meta/muse-spark-1.3": {
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"cache_read_input_token_cost": 1.5e-07,
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"input_cost_per_token": 1.25e-06,
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"litellm_provider": "meta",
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"max_input_tokens": 1048576,
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"max_output_tokens": 131072,
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"max_tokens": 131072,
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"mode": "chat",
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"output_cost_per_token": 4.25e-06,
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"search_context_cost_per_query": {
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"search_context_size_high": 0.0025,
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"search_context_size_low": 0.0025,
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"search_context_size_medium": 0.0025
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},
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"source": "https://ai.developer.meta.com/docs/pricing-rate-limits",
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"supported_endpoints": [
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"/v1/chat/completions",
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"/v1/responses",
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"/v1/messages"
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],
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"supported_modalities": [
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"text",
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"image",
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"video"
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],
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"supported_output_modalities": [
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"text"
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],
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"supports_function_calling": true,
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"supports_minimal_reasoning_effort": true,
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"supports_parallel_function_calling": true,
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"supports_pdf_input": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true,
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"supports_vision": true,
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"supports_web_search": true,
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"supports_xhigh_reasoning_effort": true
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},
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"meta/muse-spark-1.3-contributor": {
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"cache_read_input_token_cost": 2e-09,
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"input_cost_per_token": 1e-07,
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"litellm_provider": "meta",
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"max_input_tokens": 1048576,
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"max_output_tokens": 131072,
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"max_tokens": 131072,
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"mode": "chat",
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"output_cost_per_token": 2e-07,
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"search_context_cost_per_query": {
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"search_context_size_high": 0.0025,
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"search_context_size_low": 0.0025,
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"search_context_size_medium": 0.0025
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},
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"source": "https://ai.developer.meta.com/docs/pricing-rate-limits",
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"supported_endpoints": [
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"/v1/chat/completions",
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"/v1/responses",
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"/v1/messages"
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],
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"supported_modalities": [
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"text",
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"image",
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"video"
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],
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"supported_output_modalities": [
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"text"
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],
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"supports_function_calling": true,
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"supports_minimal_reasoning_effort": true,
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"supports_parallel_function_calling": true,
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"supports_pdf_input": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true,
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"supports_vision": true,
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"supports_web_search": true,
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"supports_xhigh_reasoning_effort": true
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},
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"meta_llama/Llama-3.3-70B-Instruct": {
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"litellm_provider": "meta_llama",
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"max_input_tokens": 128000,
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@ -33093,6 +33093,88 @@
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"supports_web_search": true,
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"supports_xhigh_reasoning_effort": true
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},
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"meta/muse-spark-1.3": {
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"cache_read_input_token_cost": 1.5e-07,
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"input_cost_per_token": 1.25e-06,
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"litellm_provider": "meta",
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"max_input_tokens": 1048576,
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"max_output_tokens": 131072,
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"max_tokens": 131072,
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"mode": "chat",
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"output_cost_per_token": 4.25e-06,
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"search_context_cost_per_query": {
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"search_context_size_high": 0.0025,
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"search_context_size_low": 0.0025,
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"search_context_size_medium": 0.0025
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},
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"source": "https://ai.developer.meta.com/docs/pricing-rate-limits",
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"supported_endpoints": [
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"/v1/chat/completions",
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"/v1/responses",
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"/v1/messages"
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],
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"supported_modalities": [
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"text",
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"image",
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"video"
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],
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"supported_output_modalities": [
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"text"
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],
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"supports_function_calling": true,
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"supports_minimal_reasoning_effort": true,
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"supports_parallel_function_calling": true,
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"supports_pdf_input": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true,
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"supports_vision": true,
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"supports_web_search": true,
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"supports_xhigh_reasoning_effort": true
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},
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"meta/muse-spark-1.3-contributor": {
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"cache_read_input_token_cost": 2e-09,
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"input_cost_per_token": 1e-07,
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"litellm_provider": "meta",
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"max_input_tokens": 1048576,
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"max_output_tokens": 131072,
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"max_tokens": 131072,
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"mode": "chat",
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"output_cost_per_token": 2e-07,
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"search_context_cost_per_query": {
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"search_context_size_high": 0.0025,
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"search_context_size_low": 0.0025,
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"search_context_size_medium": 0.0025
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},
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"source": "https://ai.developer.meta.com/docs/pricing-rate-limits",
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"supported_endpoints": [
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"/v1/chat/completions",
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"/v1/responses",
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"/v1/messages"
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],
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"supported_modalities": [
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"text",
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"image",
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"video"
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],
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"supported_output_modalities": [
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"text"
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],
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"supports_function_calling": true,
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"supports_minimal_reasoning_effort": true,
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"supports_parallel_function_calling": true,
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"supports_pdf_input": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true,
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"supports_vision": true,
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"supports_web_search": true,
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"supports_xhigh_reasoning_effort": true
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},
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"meta_llama/Llama-3.3-70B-Instruct": {
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"litellm_provider": "meta_llama",
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"max_input_tokens": 128000,
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107
tests/test_litellm/test_muse_spark_1_3_model_metadata.py
Normal file
107
tests/test_litellm/test_muse_spark_1_3_model_metadata.py
Normal file
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@ -0,0 +1,107 @@
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import json
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from pathlib import Path
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import pytest
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import litellm
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from litellm.cost_calculator import cost_per_token
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from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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from litellm.litellm_core_utils.llm_cost_calc.tool_call_cost_tracking import StandardBuiltInToolCostTracking
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MUSE_SPARK_STANDARD = "meta/muse-spark-1.3"
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MUSE_SPARK_CONTRIBUTOR = "meta/muse-spark-1.3-contributor"
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WEB_SEARCH_COST_PER_QUERY = 0.0025
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PRICING = (
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(MUSE_SPARK_STANDARD, 1.25e-06, 1.5e-07, 4.25e-06),
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(MUSE_SPARK_CONTRIBUTOR, 1e-07, 2e-09, 2e-07),
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)
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def _load_cost_map(filename: str = "model_prices_and_context_window.json") -> dict:
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with open(Path(__file__).parents[2] / filename) as f:
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return json.load(f)
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@pytest.mark.parametrize("model, input_cost, cached_cost, output_cost", PRICING)
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def test_muse_spark_1_3_model_info(model: str, input_cost: float, cached_cost: float, output_cost: float):
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info = _load_cost_map().get(model)
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assert info is not None, f"{model} not found in model_prices_and_context_window.json"
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assert info["litellm_provider"] == "meta"
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assert info["mode"] == "chat"
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assert info["input_cost_per_token"] == input_cost
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assert info["output_cost_per_token"] == output_cost
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assert info["cache_read_input_token_cost"] == cached_cost
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assert info["max_input_tokens"] == 1048576
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assert info["max_output_tokens"] == 131072
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assert info["max_tokens"] == 131072
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assert info["supports_function_calling"] is True
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assert info["supports_parallel_function_calling"] is True
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assert info["supports_prompt_caching"] is True
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assert info["supports_reasoning"] is True
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assert info["supports_response_schema"] is True
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assert info["supports_tool_choice"] is True
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assert info["supports_vision"] is True
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assert info["supports_pdf_input"] is True
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assert info["supports_web_search"] is True
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assert info["supports_minimal_reasoning_effort"] is True
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assert info["supports_xhigh_reasoning_effort"] is True
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assert info["supported_endpoints"] == ["/v1/chat/completions", "/v1/responses", "/v1/messages"]
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assert info["supported_modalities"] == ["text", "image", "video"]
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assert info["supported_output_modalities"] == ["text"]
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assert info["search_context_cost_per_query"] == {
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"search_context_size_high": WEB_SEARCH_COST_PER_QUERY,
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"search_context_size_low": WEB_SEARCH_COST_PER_QUERY,
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"search_context_size_medium": WEB_SEARCH_COST_PER_QUERY,
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}
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@pytest.mark.parametrize("model, input_cost, cached_cost, output_cost", PRICING)
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def test_muse_spark_1_3_cost_per_token(
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local_model_cost_map, model: str, input_cost: float, cached_cost: float, output_cost: float
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):
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prompt_cost, completion_cost = cost_per_token(model=model, prompt_tokens=1000, completion_tokens=500)
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assert prompt_cost == pytest.approx(1000 * input_cost)
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assert completion_cost == pytest.approx(500 * output_cost)
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@pytest.mark.parametrize("model", (MUSE_SPARK_STANDARD, MUSE_SPARK_CONTRIBUTOR))
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def test_muse_spark_1_3_routes_to_meta_model_api(model: str):
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routed_model, provider, _, api_base = get_llm_provider(model=model, api_key="sk-test")
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assert routed_model == model.split("/", 1)[1]
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assert provider == "meta"
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assert api_base == "https://api.meta.ai/v1"
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@pytest.mark.parametrize("model", (MUSE_SPARK_STANDARD, MUSE_SPARK_CONTRIBUTOR))
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def test_muse_spark_1_3_web_search_cost_per_query(local_model_cost_map, model: str):
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info = litellm.get_model_info(model=model)
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assert StandardBuiltInToolCostTracking.get_cost_for_web_search(model_info=info) == WEB_SEARCH_COST_PER_QUERY
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@pytest.mark.parametrize("model", (MUSE_SPARK_STANDARD, MUSE_SPARK_CONTRIBUTOR))
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def test_muse_spark_1_3_backup_matches_main(model: str):
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"""Ensure the bundled model cost map stays in sync with the canonical file."""
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main_cost = _load_cost_map()
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backup_cost = _load_cost_map("litellm/model_prices_and_context_window_backup.json")
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assert backup_cost.get(model) == main_cost.get(model), f"{model} differs between main and backup model cost maps"
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def test_muse_spark_contributor_tier_is_cheaper_than_standard():
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cost_map = _load_cost_map()
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standard = cost_map[MUSE_SPARK_STANDARD]
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contributor = cost_map[MUSE_SPARK_CONTRIBUTOR]
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for field in ("input_cost_per_token", "output_cost_per_token", "cache_read_input_token_cost"):
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assert contributor[field] < standard[field], f"contributor {field} should undercut the standard tier"
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