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fix(cognition): price swe-1.7 at the standard tier, add swe-1.7-lightning

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The cost map shipped cognition/swe-1.7 at $2.50 in / $12.50 out per million with
$1.00 cache reads. Those are the Lightning numbers. Cognition's own model list at
https://docs.devin.ai/desktop/models has uid swe-1-7 at $0.50 / $2.50 with $0.20
cache reads, and uid swe-1-7-lightning at $2.50 / $12.50 with $1.00 cache reads,
so every swe-1.7 call has been costed at 5x since the entry landed.

swe-1.7 now carries the standard rates and the Lightning tier gets its own entry,
in both cost map copies. The source field on both moves to the desktop models page,
which is the one that lists both tiers.
This commit is contained in:
mateo-berri 2026-08-20 19:41:12 -07:00
parent f1c4145f86
commit 7d999a1586
3 changed files with 72 additions and 10 deletions
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12
litellm/model_prices_and_context_window_backup.json
View file

@ -48949,6 +48949,16 @@
"source": "https://docs.devin.ai/windsurf/plugins/cascade/models"
},
"cognition/swe-1.7": {
"input_cost_per_token": 5e-07,
"output_cost_per_token": 2.5e-06,
"cache_read_input_token_cost": 2e-07,
"litellm_provider": "cognition",
"mode": "chat",
"supports_function_calling": true,
"supports_prompt_caching": true,
"source": "https://docs.devin.ai/desktop/models"
},
"cognition/swe-1.7-lightning": {
"input_cost_per_token": 2.5e-06,
"output_cost_per_token": 1.25e-05,
"cache_read_input_token_cost": 1e-06,
@ -48956,7 +48966,7 @@
"mode": "chat",
"supports_function_calling": true,
"supports_prompt_caching": true,
"source": "https://docs.devin.ai/windsurf/plugins/cascade/models"
"source": "https://docs.devin.ai/desktop/models"
},
"pinstripes/ps/glm-4.5-air": {
"max_tokens": 128000,

12
model_prices_and_context_window.json
View file

@ -48949,6 +48949,16 @@
"source": "https://docs.devin.ai/windsurf/plugins/cascade/models"
},
"cognition/swe-1.7": {
"input_cost_per_token": 5e-07,
"output_cost_per_token": 2.5e-06,
"cache_read_input_token_cost": 2e-07,
"litellm_provider": "cognition",
"mode": "chat",
"supports_function_calling": true,
"supports_prompt_caching": true,
"source": "https://docs.devin.ai/desktop/models"
},
"cognition/swe-1.7-lightning": {
"input_cost_per_token": 2.5e-06,
"output_cost_per_token": 1.25e-05,
"cache_read_input_token_cost": 1e-06,
@ -48956,7 +48966,7 @@
"mode": "chat",
"supports_function_calling": true,
"supports_prompt_caching": true,
"source": "https://docs.devin.ai/windsurf/plugins/cascade/models"
"source": "https://docs.devin.ai/desktop/models"
},
"pinstripes/ps/glm-4.5-air": {
"max_tokens": 128000,

58
tests/test_litellm/llms/openai_like/test_cognition_provider.py
View file

@ -111,33 +111,51 @@ class TestCognitionProviderIdentity:
class TestCognitionCostTracking:
@pytest.mark.parametrize(
"model, input_cost, output_cost",
"model, input_cost, output_cost, cache_read_cost",
[
("cognition/swe-1.6", 5e-07, 2.5e-06),
("cognition/swe-1.7", 2.5e-06, 1.25e-05),
("cognition/swe-1.6", 5e-07, 2.5e-06, 2e-07),
("cognition/swe-1.7", 5e-07, 2.5e-06, 2e-07),
("cognition/swe-1.7-lightning", 2.5e-06, 1.25e-05, 1e-06),
],
)
def test_cost_map_entries(self, model: str, input_cost: float, output_cost: float):
def test_cost_map_entries(self, model: str, input_cost: float, output_cost: float, cache_read_cost: float):
info = litellm.get_model_info(model=model)
assert info["litellm_provider"] == "cognition"
assert info["mode"] == "chat"
assert info["input_cost_per_token"] == input_cost
assert info["output_cost_per_token"] == output_cost
assert info["cache_read_input_token_cost"] == cache_read_cost
def test_cost_differs_from_openai_pricing(self):
@pytest.mark.parametrize(
"model, expected_prompt_cost, expected_completion_cost",
[
("cognition/swe-1.7", 0.5, 2.5),
("cognition/swe-1.7-lightning", 2.5, 12.5),
],
)
def test_cost_differs_from_openai_pricing(
self, model: str, expected_prompt_cost: float, expected_completion_cost: float
):
"""A cognition-prefixed model must never be priced off an OpenAI cost entry."""
from litellm.cost_calculator import cost_per_token
prompt_cost, completion_cost = cost_per_token(
model="cognition/swe-1.7",
model=model,
prompt_tokens=1_000_000,
completion_tokens=1_000_000,
custom_llm_provider="cognition",
)
assert prompt_cost == pytest.approx(2.5)
assert completion_cost == pytest.approx(12.5)
assert prompt_cost == pytest.approx(expected_prompt_cost)
assert completion_cost == pytest.approx(expected_completion_cost)
def test_lightning_is_five_times_the_standard_tier(self):
standard = litellm.get_model_info(model="cognition/swe-1.7")
lightning = litellm.get_model_info(model="cognition/swe-1.7-lightning")
assert lightning["input_cost_per_token"] == pytest.approx(standard["input_cost_per_token"] * 5)
assert lightning["output_cost_per_token"] == pytest.approx(standard["output_cost_per_token"] * 5)
def test_supported_endpoints_matrix(self):
matrix = json.loads((Path(litellm.__file__).parent / "provider_endpoints_support_backup.json").read_text())
@ -170,6 +188,30 @@ class TestCognitionRouting:
mock_response="hello from swe",
)
usage = response.usage
expected = usage.prompt_tokens * 5e-07 + usage.completion_tokens * 2.5e-06
assert response._hidden_params["response_cost"] == pytest.approx(expected)
@pytest.mark.asyncio
async def test_router_spend_uses_the_lightning_entry_for_lightning(self):
"""The Lightning tier is its own model, costed off its own entry."""
from litellm import Router
router = Router(
model_list=[
{
"model_name": "swe-lightning",
"litellm_params": {"model": "cognition/swe-1.7-lightning", "api_key": "sk-test"},
}
]
)
response = await router.acompletion(
model="swe-lightning",
messages=[{"role": "user", "content": "hi"}],
mock_response="hello from swe lightning",
)
usage = response.usage
expected = usage.prompt_tokens * 2.5e-06 + usage.completion_tokens * 1.25e-05
assert response._hidden_params["response_cost"] == pytest.approx(expected)