Azure — pricing & performance
Models served
51
of 1,111 tracked models
Mean output speed
46
tokens per second, averaged over
45 measured endpoints
45 measured endpoints
Mean latency
5.1s
time to first token, averaged over
45 measured endpoints
45 measured endpoints
Cheapest blended
$0.14
per 1M tokens at a 3:1
input:output blend
input:output blend
Output speed on Azure
Output tokens per second for the 45 of 51 models on Azure with published throughput telemetry, the most recent figure OpenRouter publishes for each host. The full table below lists all 51, measured or not. Higher is better. We do not run these measurements ourselves.
The Known Good
51 models on Azure
Full leaderboard →
| Model | Creator | Input $/M | Output $/M | Blended | Speed | TTFT | Context |
|---|---|---|---|---|---|---|---|
|
|
Anthropic | $10.00 | $50.00 | $20.00 | 37 | 6.1s | 1.00M |
|
|
Anthropic | $10.00 | $50.00 | $20.00 | 34 | 5.0s | 1.00M |
|
|
Anthropic | $1.00 | $5.00 | $2.00 | 67 | 0.7s | 200k |
|
|
Anthropic | $15.00 | $75.00 | $30.00 | — | — | 200k |
|
|
Anthropic | $5.00 | $25.00 | $10.00 | 73 | 1.3s | 200k |
|
|
Anthropic | $5.00 | $25.00 | $10.00 | 23 | 1.9s | 1.00M |
|
|
Anthropic | $5.00 | $25.00 | $10.00 | — | — | 1.00M |
|
|
Anthropic | $5.00 | $25.00 | $10.00 | 49 | 4.3s | 1.00M |
|
|
Anthropic | $3.00 | $15.00 | $6.00 | 42 | 1.8s | 200k |
|
|
Anthropic | $3.00 | $15.00 | $6.00 | 32 | 2.1s | 1.00M |
|
|
Anthropic | $2.00 | $10.00 | $4.00 | 65 | 0.9s | 1.00M |
|
|
Anthropic | $5.00 | $25.00 | $10.00 | 80 | 4.7s | 1.00M |
|
|
DeepSeek | $0.21 | $0.56 | $0.30 | 37 | 1.2s | 1.05M |
|
|
DeepSeek | $1.91 | $3.83 | $2.39 | 50 | 2.6s | 1.05M |
|
|
DeepSeek | $1.49 | $5.94 | $2.60 | — | — | 164k |
|
|
OpenAI | $1.00 | $2.00 | $1.25 | 30 | 0.8s | 4k |
|
|
OpenAI | $3.00 | $4.00 | $3.25 | 6 | 0.5s | 16k |
|
|
OpenAI | $30.00 | $60.00 | $37.50 | 30 | 0.5s | 8k |
|
|
OpenAI | $2.00 | $8.00 | $3.50 | 22 | 1.4s | 1.05M |
|
|
OpenAI | $0.40 | $1.60 | $0.70 | 52 | 1.3s | 1.05M |
|
|
OpenAI | $0.10 | $0.40 | $0.17 | 30 | 1.7s | 1.05M |
|
|
OpenAI | $2.50 | $10.00 | $4.38 | 38 | 0.9s | 128k |
|
|
OpenAI | $5.00 | $15.00 | $7.50 | 2 | 1.5s | 128k |
|
|
OpenAI | $2.50 | $10.00 | $4.38 | 3 | 0.6s | 128k |
|
|
OpenAI | $0.15 | $0.60 | $0.26 | 64 | 1.2s | 128k |
|
|
OpenAI | $1.25 | $10.00 | $3.44 | 59 | 11.6s | 400k |
|
|
OpenAI | $0.25 | $2.00 | $0.69 | 72 | 3.9s | 400k |
|
|
OpenAI | $0.050 | $0.40 | $0.14 | 65 | 3.4s | 400k |
|
|
OpenAI | $1.25 | $10.00 | $3.44 | 42 | 1.1s | 400k |
|
|
OpenAI | $1.25 | $10.00 | $3.44 | — | — | 128k |
|
|
OpenAI | $1.25 | $10.00 | $3.44 | 56 | 4.1s | 400k |
|
|
OpenAI | $1.25 | $10.00 | $3.44 | 49 | 4.9s | 400k |
|
|
OpenAI | $0.25 | $2.00 | $0.69 | 32 | 3.2s | 400k |
|
|
OpenAI | $1.75 | $14.00 | $4.81 | 43 | 4.4s | 400k |
|
|
OpenAI | $1.75 | $14.00 | $4.81 | — | — | 128k |
|
|
OpenAI | $1.75 | $14.00 | $4.81 | 27 | 4.6s | 400k |
|
|
OpenAI | $1.75 | $14.00 | $4.81 | — | — | 128k |
|
|
OpenAI | $1.75 | $14.00 | $4.81 | 42 | 5.7s | 400k |
|
|
OpenAI | $2.50 | $15.00 | $5.62 | 45 | 1.9s | 1.05M |
|
|
OpenAI | $0.75 | $4.50 | $1.69 | 66 | 1.6s | 400k |
|
|
OpenAI | $0.20 | $1.25 | $0.46 | 54 | 1.6s | 400k |
|
|
OpenAI | $30.00 | $180.00 | $67.50 | 2 | 9.8s | 1.05M |
|
|
OpenAI | $5.00 | $30.00 | $11.25 | 68 | 47.6s | 1.05M |
|
|
OpenAI | $0.20 | $1.20 | $0.45 | 75 | 2.8s | 1.05M |
|
|
OpenAI | $0.20 | $1.20 | $0.45 | 129 | 8.6s | 1.05M |
|
|
OpenAI | $5.00 | $30.00 | $11.25 | 46 | 4.3s | 1.05M |
|
|
OpenAI | $5.00 | $30.00 | $11.25 | 77 | 19.7s | 1.05M |
|
|
OpenAI | $2.00 | $12.00 | $4.50 | 48 | 2.1s | 1.05M |
|
|
OpenAI | $2.00 | $12.00 | $4.50 | 84 | 11.5s | 1.05M |
|
|
OpenAI | $10.00 | $50.00 | $20.00 | 19 | 8.3s | 1.05M |
|
|
OpenAI | $10.00 | $50.00 | $20.00 | 24 | 21.3s | 1.05M |
The Known Good
Source. Prices, endpoint availability and throughput for Azure are ingested from OpenRouter;
model metadata is enriched from models.dev. A blank cell means the figure was not published for that endpoint —
it never means zero. Blended price is (3 × input + output) ÷ 4, the same 3:1 blend used everywhere on this
site; see methodology. Quality scores are not provider-specific:
a model scores the same wherever it is hosted, so quality lives on the
model pages.