MoonshotAI: Kimi K2 0905
moonshotai/kimi-k2-0905
Cheapest provider
$0.60 / 1M
AtlasCloud
Fastest provider (p95)
256 tok/s
Groq
Intelligence (composite)
69.5
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 |
|---|---|---|---|---|---|---|---|
| AtlasCloud | q8· fp8 | $0.6000 | $2.5000 | 20727ms / 60242ms | 18 / 23 tok/s | 99.92% | 99.8% |
| Novita | q8· fp8 | $0.6000 | $2.5000 | 1683ms / 15218ms | 8 / 15 tok/s | 99.88% | 99.6% |
| Groq | undisclosed | $1.0000 | $3.0000 | 674ms / 5787ms | 104 / 256 tok/s | 98.96% | 94.1% |
“—” 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
82.0
broad reasoning
Code
61.0
pass@1 (HumanEval / LiveCodeBench)
AIME 2025
57.0
math accuracy
GPQA Diamond
77.0
hard reasoning
Source: Artificial Analysis (AA-aligned) via MiniMax-M2 benchmark table — Kimi K2 0905 (MMLU-Pro 82, GPQA-D 77, LiveCodeBench 61, AIME25 57); github.com/MiniMax-AI/MiniMax-M2
How Atlas routes MoonshotAI: Kimi K2 0905
- 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 MoonshotAI: Kimi K2 0905 that’s currently AtlasCloud at $0.60/1M.
- Batch tier — async, biggest discount. Roadmapped to use provider batch APIs (OpenAI / Anthropic) where available and queued spot capacity for open-weight workloads.