OpenAI: GPT-5
openai/gpt-5
Cheapest provider
$1.25 / 1M
Azure
Fastest provider (p95)
—
No throughput data yet — populated as traffic accumulates
Intelligence (composite)
87.8
MMLU-Pro · HumanEval · math · GPQA
Per-provider performance
Latency / throughput / uptime measured across providers over the last 30 minutes of live traffic. Atlas’s router weighs these per call (with the eval-gate signal) when picking a variant for Standard and Batch tiers.
| Provider | Quant | Input $/1M | Output $/1M | Latency p50 / p95 | Throughput p50 / p95 | Uptime 30m | Success |
|---|---|---|---|---|---|---|---|
| Azure | full· unknown | $1.2500 | $10.0000 | — | — | — | — |
| Azure | full· unknown | $1.2500 | $10.0000 | — | — | — | — |
| OpenAI | full· unknown | $1.2500 | $10.0000 | — | — | 99.92% | — |
“—” 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
87.0
broad reasoning
Code
85.0
pass@1 (HumanEval / LiveCodeBench)
AIME 2025
94.0
math accuracy
GPQA Diamond
85.0
hard reasoning
Source: Artificial Analysis (AA-aligned) — GPT-5 thinking (MMLU-Pro 87, GPQA-D 85, LiveCodeBench 85, AIME25 94); via MiniMax-M2 table + GPT-5 system card
How Atlas routes OpenAI: GPT-5
- Realtime tier — direct passthrough at the upstream’s native precision. Best for hard latency / quality guarantees.
- Standard tier — Atlas picks the cheapest provider variant whose quantization has stayed green on your operation’s eval gates. For OpenAI: GPT-5 that’s currently Azure at $1.25/1M.
- Batch tier — async, biggest discount. Roadmapped to use provider batch APIs (OpenAI / Anthropic) where available and queued spot capacity for open-weight workloads.