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feat(pricing): add GovCloud rows for every live but unpriced Bedrock model

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Every model bedrock list-foundation-models and list-inference-profiles
report as live in us-gov-west-1 or us-gov-east-1 now has a priced row:
Claude Fable 5.1 (profile plus in-region), Nemotron Nano 9B (profile plus
in-region), Grok 4.6 (profile plus Mantle in both regions), the us-gov.
Claude 3 Haiku profile in the east, Nova Lite, Micro and the Nova 2
multimodal embeddings in the west, and the Gemma 4 and gpt-oss Mantle
SKUs the GovCloud offer files price. Offer-file rates are used where AWS
publishes them; Claude rows carry the 1.2x GovCloud premium.
This commit is contained in:
mateo-berri 2026-09-04 10:03:43 -07:00
parent 46974fe46e
commit bef3585d82
4 changed files with 909 additions and 4 deletions
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374
litellm/model_prices_and_context_window_backup.json
View file

@ -11957,6 +11957,48 @@
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@ -42445,6 +42504,39 @@
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@ -42470,6 +42562,16 @@
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@ -42510,6 +42612,21 @@
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@ -58345,6 +58472,39 @@
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@ -58619,6 +58822,120 @@
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@ -58646,6 +58963,63 @@
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374
model_prices_and_context_window.json
View file

@ -11957,6 +11957,48 @@
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},
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@ -42320,6 +42362,23 @@
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@ -42445,6 +42504,39 @@
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@ -42470,6 +42562,16 @@
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"max_input_tokens": 128000,
"max_output_tokens": 8192,
"max_tokens": 8192,
"mode": "chat",
"output_cost_per_token": 2.76e-07,
"supports_system_messages": true
},
"us-gov.nvidia.nemotron-super-3-120b": {
"input_cost_per_token": 1.8e-07,
"litellm_provider": "bedrock_converse",
@ -42510,6 +42612,21 @@
"supports_response_schema": true,
"supports_tool_choice": true
},
"us-gov.xai.grok-4.6": {
"input_cost_per_token": 2.64e-06,
"output_cost_per_token": 7.92e-06,
"cache_read_input_token_cost": 6.6e-07,
"litellm_provider": "bedrock_converse",
"max_input_tokens": 500000,
"max_output_tokens": 500000,
"max_tokens": 500000,
"mode": "chat",
"supports_function_calling": true,
"supports_prompt_caching": false,
"supports_reasoning": true,
"supports_tool_choice": true,
"supports_vision": true
},
"au.anthropic.claude-haiku-4-5-20251001-v1:0": {
"cache_creation_input_token_cost": 1.375e-06,
"cache_creation_input_token_cost_above_1hr": 2.2e-06,
@ -58210,6 +58327,16 @@
"supports_system_messages": true,
"supports_vision": true
},
"bedrock/us-gov-west-1/nvidia.nemotron-nano-9b-v2": {
"input_cost_per_token": 7.2e-08,
"litellm_provider": "bedrock",
"max_input_tokens": 128000,
"max_output_tokens": 8192,
"max_tokens": 8192,
"mode": "chat",
"output_cost_per_token": 2.76e-07,
"supports_system_messages": true
},
"bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b": {
"input_cost_per_token": 1.8e-07,
"litellm_provider": "bedrock",
@ -58345,6 +58472,39 @@
"supports_vision": true,
"supports_xhigh_reasoning_effort": true
},
"bedrock/us-gov-west-1/anthropic.claude-fable-5-1": {
"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,
"input_cost_per_token": 1.2e-05,
"litellm_provider": "bedrock",
"max_input_tokens": 1000000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"output_cost_per_token": 6e-05,
"supports_adaptive_thinking": true,
"thinking_always_on": true,
"supports_mid_conversation_system": true,
"supports_assistant_prefill": false,
"supports_computer_use": true,
"supports_forced_tool_use": false,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_sampling_params": false,
"supports_tool_choice": true,
"supports_vision": true,
"supports_xhigh_reasoning_effort": true,
"supports_native_structured_output": false,
"supports_max_reasoning_effort": true,
"supports_output_config": true,
"bedrock_output_config_effort_ceiling": "xhigh",
"supports_parallel_tool_use_config": true,
"prompt_cache_min_tokens": 512
},
"bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b": {
"input_cost_per_token": 7.2e-08,
"litellm_provider": "bedrock",
@ -58370,6 +58530,16 @@
"supports_system_messages": true,
"supports_vision": true
},
"bedrock/us-gov-east-1/nvidia.nemotron-nano-9b-v2": {
"input_cost_per_token": 7.2e-08,
"litellm_provider": "bedrock",
"max_input_tokens": 128000,
"max_output_tokens": 8192,
"max_tokens": 8192,
"mode": "chat",
"output_cost_per_token": 2.76e-07,
"supports_system_messages": true
},
"bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b": {
"input_cost_per_token": 1.8e-07,
"litellm_provider": "bedrock",
@ -58505,6 +58675,39 @@
"supports_vision": true,
"supports_xhigh_reasoning_effort": true
},
"bedrock/us-gov-east-1/anthropic.claude-fable-5-1": {
"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,
"input_cost_per_token": 1.2e-05,
"litellm_provider": "bedrock",
"max_input_tokens": 1000000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"output_cost_per_token": 6e-05,
"supports_adaptive_thinking": true,
"thinking_always_on": true,
"supports_mid_conversation_system": true,
"supports_assistant_prefill": false,
"supports_computer_use": true,
"supports_forced_tool_use": false,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_sampling_params": false,
"supports_tool_choice": true,
"supports_vision": true,
"supports_xhigh_reasoning_effort": true,
"supports_native_structured_output": false,
"supports_max_reasoning_effort": true,
"supports_output_config": true,
"bedrock_output_config_effort_ceiling": "xhigh",
"supports_parallel_tool_use_config": true,
"prompt_cache_min_tokens": 512
},
"bedrock_mantle/us-gov-west-1/openai.gpt-5.6-terra": {
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 1050000,
@ -58619,6 +58822,120 @@
"output_cost_per_token": 3e-06,
"cache_read_input_token_cost": 2.4e-07
},
"bedrock_mantle/us-gov-west-1/xai.grok-4.6": {
"use_openai_responses_path": true,
"input_cost_per_token": 2.64e-06,
"output_cost_per_token": 7.92e-06,
"cache_read_input_token_cost": 6.6e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 500000,
"max_output_tokens": 500000,
"max_tokens": 500000,
"mode": "chat",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"bedrock_mantle/us-gov-west-1/google.gemma-4-e2b": {
"input_cost_per_token": 4.8e-08,
"output_cost_per_token": 9.6e-08,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 128000,
"max_output_tokens": 128000,
"max_tokens": 128000,
"mode": "chat",
"use_openai_responses_path": true,
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_parallel_function_calling": false,
"supports_reasoning": true,
"supports_tool_choice": true,
"supports_vision": true
},
"bedrock_mantle/us-gov-west-1/google.gemma-4-26b-a4b": {
"input_cost_per_token": 1.56e-07,
"output_cost_per_token": 4.8e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 256000,
"max_output_tokens": 256000,
"max_tokens": 256000,
"mode": "chat",
"use_openai_responses_path": true,
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_parallel_function_calling": false,
"supports_reasoning": true,
"supports_tool_choice": true,
"supports_vision": true
},
"bedrock_mantle/us-gov-west-1/google.gemma-4-31b": {
"input_cost_per_token": 1.68e-07,
"output_cost_per_token": 4.8e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 256000,
"max_output_tokens": 256000,
"max_tokens": 256000,
"mode": "chat",
"use_openai_responses_path": true,
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_parallel_function_calling": false,
"supports_reasoning": true,
"supports_tool_choice": true,
"supports_vision": true
},
"bedrock_mantle/us-gov-west-1/openai.gpt-oss-20b": {
"input_cost_per_token": 8.4e-08,
"output_cost_per_token": 3.6e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 131072,
"max_output_tokens": 32768,
"max_tokens": 32768,
"mode": "chat",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_parallel_function_calling": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true
},
"bedrock_mantle/us-gov-west-1/openai.gpt-oss-120b": {
"input_cost_per_token": 1.8e-07,
"output_cost_per_token": 7.2e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 131072,
"max_output_tokens": 32768,
"max_tokens": 32768,
"mode": "chat",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_parallel_function_calling": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true
},
"bedrock_mantle/us-gov-east-1/openai.gpt-5.4": {
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 1050000,
@ -58646,6 +58963,63 @@
"cache_read_input_token_cost": 3.3e-07,
"output_cost_per_token": 1.98e-05
},
"bedrock_mantle/us-gov-east-1/xai.grok-4.6": {
"use_openai_responses_path": true,
"input_cost_per_token": 2.64e-06,
"output_cost_per_token": 7.92e-06,
"cache_read_input_token_cost": 6.6e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 500000,
"max_output_tokens": 500000,
"max_tokens": 500000,
"mode": "chat",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"bedrock_mantle/us-gov-east-1/openai.gpt-oss-20b": {
"input_cost_per_token": 8.4e-08,
"output_cost_per_token": 3.6e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 131072,
"max_output_tokens": 32768,
"max_tokens": 32768,
"mode": "chat",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_parallel_function_calling": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true
},
"bedrock_mantle/us-gov-east-1/openai.gpt-oss-120b": {
"input_cost_per_token": 1.8e-07,
"output_cost_per_token": 7.2e-07,
"litellm_provider": "bedrock_mantle",
"max_input_tokens": 131072,
"max_output_tokens": 32768,
"max_tokens": 32768,
"mode": "chat",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses"
],
"supports_function_calling": true,
"supports_parallel_function_calling": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true
},
"azure/us-gov/gpt-5.1": {
"cache_read_input_token_cost": 1.71875e-07,
"default_reasoning_effort": "none",

157
tests/test_litellm/test_bedrock_usgov_pricing.py
View file

@ -139,6 +139,13 @@ CLAUDE_GOV_EXPECTED = {
"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,
},
}
@ -152,9 +159,11 @@ 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_pricing(model_data, key_template, expected_provider, base_key):
"""Sonnet 5, Opus 4.8, and Opus 5 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 in the GovCloud offer file (1.2x global).
"""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}"
@ -169,6 +178,7 @@ def test_usgov_claude_pricing(model_data, key_template, expected_provider, base_
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),
@ -268,6 +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
@ -219,17 +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-west-1/anthropic.claude-opus-5
bedrock/us-gov-east-1/anthropic.claude-opus-5
bedrock/us-gov-east-1/anthropic.claude-fable-5-1