DeepSeek: R1
deepseek/deepseek-r1
Cheapest provider
$0.70 / 1M
Novita
Fastest provider (p95)
87 tok/s
Azure
Intelligence (composite)
72.9
MMLU-Pro · HumanEval · math · GPQA
Per-provider performance
Latency / throughput / uptime / price measured across providers over the last 30 minutes of live traffic. This is what proves “sourced cheapest” — Atlas mode draws on these per call to serve the cheapest path that holds quality.
| Provider | Quant | Input $/1M | Output $/1M | Latency p50 / p95 | Throughput p50 / p95 | Uptime 30m | Success |
|---|---|---|---|---|---|---|---|
| Novita | q8· fp8 | $0.7000 | $2.5000 | 2020ms / 6022ms | 25 / 28 tok/s | 98.93% | 98.9% |
| Azure | undisclosed | $1.4850 | $5.9400 | 1985ms / 10299ms | 55 / 86.6 tok/s | 94.03% | 94.0% |
“—” means live telemetry hasn’t accumulated enough recent traffic for that endpoint. “undisclosed” means the provider serves the model but doesn’t expose the quantization label (typically running fp8 / int8 internally).
Intelligence breakdown
Composite score is a weighted average of public benchmarks (30% MMLU-Pro, 25% code pass@1, 25% math, 20% GPQA). Numbers come from model cards and the Artificial Analysis intelligence harness; missing components are renormalised over what’s present.
MMLU-Pro
84.0
broad reasoning
Code
63.5
pass@1 (HumanEval / LiveCodeBench)
AIME 2025
70.0
math accuracy
GPQA Diamond
71.5
hard reasoning
Source: DeepSeek-R1 model card (MMLU-Pro 84.0, GPQA-Diamond 71.5, LiveCodeBench 63.5, AIME25 70.0); huggingface.co/deepseek-ai/DeepSeek-R1-0528
How Atlas mode sources DeepSeek: R1
- Strict mode — pin DeepSeek: R1 exactly and we pass it straight through, sourced from the cheapest provider above. The same model, no substitutions — currently Novita at $0.70/1M.
- Atlas mode — the default. Each call is auto-optimized for the cheapest path that holds quality, at least 5% off going direct from call one and climbing as it ramps. You always see which model served the call and exactly what you saved — thumbs-down anything you don’t like for a full refund.