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Merge pull request #39764 from BerriAI/litellm_govcloud_profiles_lit6421

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feat(pricing): add GovCloud pricing for every live but unpriced Bedrock model
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Mateo Wang 2026-09-05 17:15:22 -07:00 • committed by GitHub
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4 changed files with 1242 additions and 10 deletions
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litellm/model_prices_and_context_window_backup.json
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@ -12238,6 +12238,48 @@
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532
model_prices_and_context_window.json
View file

@ -12238,6 +12238,48 @@
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180
tests/test_litellm/test_bedrock_usgov_pricing.py
View file

@ -132,6 +132,20 @@ CLAUDE_GOV_EXPECTED = {
"cache_creation_input_token_cost_above_1hr": 1.2e-05,
"cache_read_input_token_cost": 6e-07,
},
"anthropic.claude-opus-5": {
"input_cost_per_token": 6e-06,
"output_cost_per_token": 3e-05,
"cache_creation_input_token_cost": 7.5e-06,
"cache_creation_input_token_cost_above_1hr": 1.2e-05,
"cache_read_input_token_cost": 6e-07,
},
"anthropic.claude-fable-5-1": {
"input_cost_per_token": 1.2e-05,
"output_cost_per_token": 6e-05,
"cache_creation_input_token_cost": 1.5e-05,
"cache_creation_input_token_cost_above_1hr": 2.4e-05,
"cache_read_input_token_cost": 3e-07,
},
}
@ -144,15 +158,18 @@ USGOV_CLAUDE_KEY_TEMPLATES = {
@pytest.mark.parametrize("base_key", CLAUDE_GOV_EXPECTED)
@pytest.mark.parametrize("key_template,expected_provider", USGOV_CLAUDE_KEY_TEMPLATES.items())
def test_usgov_claude_sonnet5_opus48_pricing(model_data, key_template, expected_provider, base_key):
"""Sonnet 5 and Opus 4.8 gov entries, both in-region keys and the us-gov.
geo inference profile the model cards list for GovCloud, must match the
rates AWS publishes on the Bedrock pricing page (1.2x global).
def test_usgov_claude_pricing(model_data, key_template, expected_provider, base_key):
"""Sonnet 5, Opus 4.8, Opus 5, and Fable 5.1 gov entries, both in-region keys
and the us-gov. geo inference profile the model cards list for GovCloud, must
carry the 1.2x GovCloud premium over the global anthropic.* rates. No public
AWS source (offer files, pricing page) lists Claude GovCloud rows; the premium
is the one AWS quotes for Opus 4.8 in GovCloud ($6/$30 per million).
"""
gov_key = key_template.format(base_key=base_key)
assert gov_key in model_data, f"Missing model entry: {gov_key}"
info = model_data[gov_key]
assert info["litellm_provider"] == expected_provider
assert "search_context_cost_per_query" not in info
for field, expected in CLAUDE_GOV_EXPECTED[base_key].items():
assert info[field] == expected, f"{gov_key}: {field} should be {expected} (got {info[field]})"
ratio = info[field] / model_data[base_key][field]
@ -161,6 +178,7 @@ def test_usgov_claude_sonnet5_opus48_pricing(model_data, key_template, expected_
CONVERSE_GOV_EXPECTED = {
"nvidia.nemotron-nano-3-30b": (7.2e-08, 2.88e-07),
"nvidia.nemotron-nano-9b-v2": (7.2e-08, 2.76e-07),
"nvidia.nemotron-nano-12b-v2": (2.4e-07, 7.2e-07),
"nvidia.nemotron-super-3-120b": (1.8e-07, 7.8e-07),
"openai.gpt-oss-20b-1:0": (8.4e-08, 3.6e-07),
@ -169,18 +187,19 @@ CONVERSE_GOV_EXPECTED = {
@pytest.mark.parametrize("base_key", CONVERSE_GOV_EXPECTED)
@pytest.mark.parametrize("region", ["us-gov-east-1", "us-gov-west-1"])
def test_usgov_converse_model_pricing(model_data, region, base_key):
"""Nemotron and gpt-oss gov entries must match the AWS Bedrock offer file,
which prices both GovCloud regions identically at 1.2x commercial.
@pytest.mark.parametrize("key_template,expected_provider", USGOV_CLAUDE_KEY_TEMPLATES.items())
def test_usgov_converse_model_pricing(model_data, key_template, expected_provider, base_key):
"""Nemotron and gpt-oss gov entries, in-region and the us-gov. geo inference
profile both GovCloud regions list as ACTIVE, must match the AWS Bedrock
offer file, which prices both regions identically at 1.2x commercial.
"""
gov_key = f"bedrock/{region}/{base_key}"
gov_key = key_template.format(base_key=base_key)
assert gov_key in model_data, f"Missing model entry: {gov_key}"
info = model_data[gov_key]
expected_input, expected_output = CONVERSE_GOV_EXPECTED[base_key]
assert info["input_cost_per_token"] == expected_input
assert info["output_cost_per_token"] == expected_output
assert info["litellm_provider"] == "bedrock"
assert info["litellm_provider"] == expected_provider
base = model_data[base_key]
assert abs(info["input_cost_per_token"] / base["input_cost_per_token"] - 1.2) < 1e-9
assert abs(info["output_cost_per_token"] / base["output_cost_per_token"] - 1.2) < 1e-9
@ -259,6 +278,147 @@ def test_usgov_mantle_grok_4_3_west_only(model_data):
assert "bedrock_mantle/us-gov-east-1/xai.grok-4.3" not in model_data
def test_usgov_east_haiku_profile_mirrors_in_region_row(model_data):
"""us-gov-east-1 serves claude-3-haiku through the us-gov. inference profile
only, so the profile row must bill exactly like the in-region gov row.
"""
profile = model_data["us-gov.anthropic.claude-3-haiku-20240307-v1:0"]
in_region = model_data["bedrock/us-gov-east-1/anthropic.claude-3-haiku-20240307-v1:0"]
assert profile["litellm_provider"] == "bedrock_converse"
assert {k: v for k, v in profile.items() if k != "litellm_provider"} == {
k: v for k, v in in_region.items() if k != "litellm_provider"
}
GROK_4_6_GOV_KEYS = {
"us-gov.xai.grok-4.6": ("us.xai.grok-4.6", "bedrock_converse"),
"bedrock_mantle/us-gov-west-1/xai.grok-4.6": ("bedrock_mantle/xai.grok-4.6", "bedrock_mantle"),
"bedrock_mantle/us-gov-east-1/xai.grok-4.6": ("bedrock_mantle/xai.grok-4.6", "bedrock_mantle"),
}
@pytest.mark.parametrize("gov_key", GROK_4_6_GOV_KEYS)
def test_usgov_grok_4_6_pricing(model_data, gov_key):
"""Both GovCloud regions serve grok-4.6 through the us-gov. profile only, and
both offer files price its standard SKU at 1.2x the commercial US rate.
"""
base_key, expected_provider = GROK_4_6_GOV_KEYS[gov_key]
assert gov_key in model_data, f"Missing model entry: {gov_key}"
info = model_data[gov_key]
assert info["litellm_provider"] == expected_provider
assert info["input_cost_per_token"] == 2.64e-06
assert info["output_cost_per_token"] == 7.92e-06
assert info["cache_read_input_token_cost"] == 6.6e-07
for field in ("input_cost_per_token", "output_cost_per_token", "cache_read_input_token_cost"):
assert abs(info[field] / model_data[base_key][field] - 1.2) < 1e-9
NOVA_GOV_WEST_EXPECTED = {
"amazon.nova-lite-v1:0": (7.2e-08, 2.88e-07),
"amazon.nova-micro-v1:0": (4.2e-08, 1.68e-07),
}
@pytest.mark.parametrize("base_key", NOVA_GOV_WEST_EXPECTED)
def test_usgov_west_nova_lite_micro_pricing(model_data, base_key):
"""Nova Lite and Micro are on-demand in us-gov-west-1 only; the offer file
prices them at 1.2x commercial, like the Nova Pro row that was already there.
"""
gov_key = f"bedrock/us-gov-west-1/{base_key}"
assert gov_key in model_data, f"Missing model entry: {gov_key}"
info = model_data[gov_key]
expected_input, expected_output = NOVA_GOV_WEST_EXPECTED[base_key]
assert info["litellm_provider"] == "bedrock"
assert info["input_cost_per_token"] == expected_input
assert info["output_cost_per_token"] == expected_output
assert abs(info["input_cost_per_token"] / model_data[base_key]["input_cost_per_token"] - 1.2) < 1e-9
assert abs(info["output_cost_per_token"] / model_data[base_key]["output_cost_per_token"] - 1.2) < 1e-9
assert f"bedrock/us-gov-east-1/{base_key}" not in model_data
def test_usgov_west_nova_2_multimodal_embeddings_pricing(model_data):
"""Every meter of the multimodal embedding model (tokens, images, audio and
video seconds) carries the 1.2x uplift the us-gov-west-1 offer file lists.
"""
gov_key = "bedrock/us-gov-west-1/amazon.nova-2-multimodal-embeddings-v1:0"
assert gov_key in model_data, f"Missing model entry: {gov_key}"
info = model_data[gov_key]
assert info["litellm_provider"] == "bedrock"
assert info["mode"] == "embedding"
assert info["input_cost_per_token"] == 1.62e-07
assert info["input_cost_per_image"] == 7.2e-05
assert info["input_cost_per_audio_per_second"] == 0.000168
assert info["input_cost_per_video_per_second"] == 0.00084
assert "bedrock/us-gov-east-1/amazon.nova-2-multimodal-embeddings-v1:0" not in model_data
MANTLE_GOV_FLAT_EXPECTED = {
"google.gemma-4-e2b": (4.8e-08, 9.6e-08, ("us-gov-west-1",)),
"google.gemma-4-26b-a4b": (1.56e-07, 4.8e-07, ("us-gov-west-1",)),
"google.gemma-4-31b": (1.68e-07, 4.8e-07, ("us-gov-west-1",)),
"openai.gpt-oss-20b": (8.4e-08, 3.6e-07, ("us-gov-west-1", "us-gov-east-1")),
"openai.gpt-oss-120b": (1.8e-07, 7.2e-07, ("us-gov-west-1", "us-gov-east-1")),
}
@pytest.mark.parametrize("model", MANTLE_GOV_FLAT_EXPECTED)
def test_usgov_mantle_gemma_and_gpt_oss_pricing(model_data, model):
"""Gemma 4 is priced in the us-gov-west-1 offer file only and gpt-oss in both;
each Mantle gov row carries the offer file's standard SKU, and no row exists
for a region whose offer file has no SKU.
"""
expected_input, expected_output, regions = MANTLE_GOV_FLAT_EXPECTED[model]
for region in ("us-gov-west-1", "us-gov-east-1"):
gov_key = f"bedrock_mantle/{region}/{model}"
if region not in regions:
assert gov_key not in model_data
continue
assert gov_key in model_data, f"Missing model entry: {gov_key}"
info = model_data[gov_key]
assert info["litellm_provider"] == "bedrock_mantle"
assert info["input_cost_per_token"] == expected_input
assert info["output_cost_per_token"] == expected_output
GOV_ROW_SOURCES = {
"us-gov.anthropic.claude-fable-5-1": "anthropic.claude-fable-5-1",
"bedrock/us-gov-west-1/anthropic.claude-fable-5-1": "anthropic.claude-fable-5-1",
"bedrock/us-gov-east-1/anthropic.claude-fable-5-1": "anthropic.claude-fable-5-1",
"us-gov.nvidia.nemotron-nano-9b-v2": "nvidia.nemotron-nano-9b-v2",
"bedrock/us-gov-west-1/nvidia.nemotron-nano-9b-v2": "nvidia.nemotron-nano-9b-v2",
"bedrock/us-gov-east-1/nvidia.nemotron-nano-9b-v2": "nvidia.nemotron-nano-9b-v2",
"us-gov.xai.grok-4.6": "us.xai.grok-4.6",
"bedrock_mantle/us-gov-west-1/xai.grok-4.6": "bedrock_mantle/xai.grok-4.6",
"bedrock_mantle/us-gov-east-1/xai.grok-4.6": "bedrock_mantle/xai.grok-4.6",
"bedrock/us-gov-west-1/amazon.nova-2-multimodal-embeddings-v1:0": "amazon.nova-2-multimodal-embeddings-v1:0",
"bedrock/us-gov-west-1/amazon.nova-lite-v1:0": "amazon.nova-lite-v1:0",
"bedrock/us-gov-west-1/amazon.nova-micro-v1:0": "amazon.nova-micro-v1:0",
"bedrock_mantle/us-gov-west-1/google.gemma-4-e2b": "bedrock_mantle/google.gemma-4-e2b",
"bedrock_mantle/us-gov-west-1/google.gemma-4-26b-a4b": "bedrock_mantle/google.gemma-4-26b-a4b",
"bedrock_mantle/us-gov-west-1/google.gemma-4-31b": "bedrock_mantle/google.gemma-4-31b",
"bedrock_mantle/us-gov-west-1/openai.gpt-oss-20b": "bedrock_mantle/openai.gpt-oss-20b",
"bedrock_mantle/us-gov-east-1/openai.gpt-oss-20b": "bedrock_mantle/openai.gpt-oss-20b",
"bedrock_mantle/us-gov-west-1/openai.gpt-oss-120b": "bedrock_mantle/openai.gpt-oss-120b",
"bedrock_mantle/us-gov-east-1/openai.gpt-oss-120b": "bedrock_mantle/openai.gpt-oss-120b",
}
def _non_pricing_fields(info):
return {k: v for k, v in info.items() if "cost" not in k and k not in ("litellm_provider", "source")}
@pytest.mark.parametrize("gov_key", GOV_ROW_SOURCES)
def test_usgov_rows_keep_commercial_limits_and_capabilities(model_data, gov_key):
"""A gov row differs from the commercial row it mirrors only in price and
provider: context limits, mode, and capability flags stay identical, so a
hand-copied row cannot silently drop tool calling or shrink the context window.
"""
gov = model_data[gov_key]
assert _non_pricing_fields(gov) == _non_pricing_fields(model_data[GOV_ROW_SOURCES[gov_key]])
assert "search_context_cost_per_query" not in gov
assert "source" not in gov
AZURE_GOV_EXPECTED = {
"azure/us-gov/gpt-5.1": {
"input_cost_per_token": 1.71875e-06,

8
whitelisted_bedrock_models.txt
View file

@ -138,6 +138,8 @@ bedrock/us-gov-east-1/anthropic.claude-sonnet-4-5-20250929-v1:0
bedrock/us-gov-east-1/claude-sonnet-4-5-20250929-v1:0
bedrock/us-gov-east-1/meta.llama3-70b-instruct-v1:0
bedrock/us-gov-east-1/meta.llama3-8b-instruct-v1:0
bedrock/us-gov-west-1/amazon.nova-lite-v1:0
bedrock/us-gov-west-1/amazon.nova-micro-v1:0
bedrock/us-gov-west-1/amazon.nova-pro-v1:0
bedrock/us-gov-west-1/amazon.titan-text-express-v1
bedrock/us-gov-west-1/amazon.titan-text-lite-v1
@ -219,15 +221,21 @@ bedrock/us-gov-east-1/anthropic.claude-haiku-4-5-20251001-v1:0
bedrock/us-gov-west-1/anthropic.claude-haiku-4-5-20251001-v1:0
bedrock/us-gov-west-1/nvidia.nemotron-nano-3-30b
bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2
bedrock/us-gov-west-1/nvidia.nemotron-nano-9b-v2
bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b
bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0
bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0
bedrock/us-gov-west-1/anthropic.claude-sonnet-5
bedrock/us-gov-west-1/anthropic.claude-opus-4-8
bedrock/us-gov-west-1/anthropic.claude-opus-5
bedrock/us-gov-west-1/anthropic.claude-fable-5-1
bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b
bedrock/us-gov-east-1/nvidia.nemotron-nano-12b-v2
bedrock/us-gov-east-1/nvidia.nemotron-nano-9b-v2
bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b
bedrock/us-gov-east-1/openai.gpt-oss-20b-1:0
bedrock/us-gov-east-1/openai.gpt-oss-120b-1:0
bedrock/us-gov-east-1/anthropic.claude-sonnet-5
bedrock/us-gov-east-1/anthropic.claude-opus-4-8
bedrock/us-gov-east-1/anthropic.claude-opus-5
bedrock/us-gov-east-1/anthropic.claude-fable-5-1