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feat(cost-map): add meta/muse-ember-1.0 with long-context rates from the Meta pricing page (#50847)
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
Kerry Lu
GitHub
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d1a0cc6b24
3 changed files with 165 additions and 0 deletions
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@ -42601,6 +42601,52 @@
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"supports_function_calling": true,
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"supports_tool_choice": false
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},
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"meta/muse-ember-1.0": {
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"cache_read_input_token_cost": 4e-09,
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"cache_read_input_token_cost_above_200k_tokens": 1.2e-08,
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"input_cost_per_token": 1e-07,
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"input_cost_per_token_above_200k_tokens": 3e-07,
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"litellm_provider": "meta",
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"max_input_tokens": 1048576,
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"max_output_tokens": 524288,
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"mode": "chat",
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"output_cost_per_token": 5e-07,
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"output_cost_per_token_above_200k_tokens": 1.5e-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://dev.meta.ai/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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"audio"
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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_max_reasoning_effort": true,
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"supports_minimal_reasoning_effort": true,
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"supports_none_reasoning_effort": false,
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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-1.1": {
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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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@ -42601,6 +42601,52 @@
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"supports_function_calling": true,
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"supports_tool_choice": false
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},
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"meta/muse-ember-1.0": {
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"cache_read_input_token_cost": 4e-09,
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"cache_read_input_token_cost_above_200k_tokens": 1.2e-08,
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"input_cost_per_token": 1e-07,
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"input_cost_per_token_above_200k_tokens": 3e-07,
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"litellm_provider": "meta",
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"max_input_tokens": 1048576,
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"max_output_tokens": 524288,
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"mode": "chat",
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"output_cost_per_token": 5e-07,
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"output_cost_per_token_above_200k_tokens": 1.5e-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://dev.meta.ai/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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"audio"
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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_max_reasoning_effort": true,
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"supports_minimal_reasoning_effort": true,
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"supports_none_reasoning_effort": false,
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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-1.1": {
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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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73
tests/unit/test_muse_ember_1_0_model_metadata.py
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73
tests/unit/test_muse_ember_1_0_model_metadata.py
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@ -0,0 +1,73 @@
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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.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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from litellm.litellm_core_utils.reasoning_effort_capability import resolve_supported_reasoning_efforts
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MUSE_EMBER = "meta/muse-ember-1.0"
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LONG_CONTEXT_THRESHOLD = 200_000
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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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def test_muse_ember_routes_to_meta_model_api():
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routed_model, provider, _, api_base = get_llm_provider(model=MUSE_EMBER, api_key="sk-test")
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assert routed_model == "muse-ember-1.0"
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assert provider == "meta"
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assert api_base == "https://api.meta.ai/v1"
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def test_muse_ember_backup_matches_main():
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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 main_cost[MUSE_EMBER] == backup_cost.get(MUSE_EMBER)
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def test_muse_ember_reasoning_efforts_include_max_and_exclude_none():
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entry = dict(_load_cost_map()[MUSE_EMBER])
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entry["key"] = MUSE_EMBER
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resolved = resolve_supported_reasoning_efforts(entry, deployment_is_mapped=True)
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assert resolved is not None
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assert "max" in resolved
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assert "xhigh" in resolved
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assert "none" not in resolved
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def test_muse_ember_long_context_tier_costs_more_than_standard():
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row = _load_cost_map()[MUSE_EMBER]
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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 row[f"{field}_above_200k_tokens"] > row[field], f"{field} long-context rate should exceed the base rate"
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def test_muse_ember_bills_long_context_rates_above_200k_input_tokens():
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row = _load_cost_map()[MUSE_EMBER]
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completion_tokens = 1_000
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standard_prompt = LONG_CONTEXT_THRESHOLD
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standard_cost = sum(
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litellm.cost_per_token(model=MUSE_EMBER, prompt_tokens=standard_prompt, completion_tokens=completion_tokens)
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)
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assert standard_cost == pytest.approx(
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standard_prompt * row["input_cost_per_token"] + completion_tokens * row["output_cost_per_token"]
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)
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long_prompt = LONG_CONTEXT_THRESHOLD + 50_000
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long_cost = sum(
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litellm.cost_per_token(model=MUSE_EMBER, prompt_tokens=long_prompt, completion_tokens=completion_tokens)
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)
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assert long_cost == pytest.approx(
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long_prompt * row["input_cost_per_token_above_200k_tokens"]
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+ completion_tokens * row["output_cost_per_token_above_200k_tokens"]
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)
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assert long_cost > 3 * standard_cost
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