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MoonshotAI: Kimi K3 Performance

Try Kimi K3 on us. Starter credit covers your first requests, then one key reaches all 28 provider routes with automatic failover.

moonshotai/kimi-k3

open weights Performance

All models

AI IQ IQ 127 #22 public AI IQ rank for kimi-k3
View AI IQ profile

Measured performance

Continuously sampled p50/p95 time-to-first-token (TTFT), effective throughput, and success rate for MoonshotAI: Kimi K3. Effective throughput uses provider-reported output tokens over complete request time. Unsupported route and probe-configuration rows are separated from provider downtime, and no prompt or output content is stored.

Providerp50 TTFTp95 TTFTEffective throughputUptimeConfig excludedAvailability samples
sail-research 1674 ms 1837 ms 132 tok/s n=1 66.67% — 12
relace 1882 ms 8072 ms 57 tok/s n=1 100.00% — 15
kimi 8848 ms 13618 ms — 100.00% — 10
together 838 ms 4545 ms 34 tok/s n=1 100.00% — 2
tinfoil 996 ms 1117 ms 89 tok/s n=1 100.00% — 2
telnyx 1052 ms 2483 ms 139 tok/s n=2 100.00% — 2
engy 1272 ms 2159 ms 59 tok/s n=2 100.00% — 6
makora 1999 ms 2153 ms 29 tok/s n=1 100.00% — 5
akashml 2206 ms 11914 ms 139 tok/s n=1 100.00% — 8
tencent 2538 ms 4195 ms 33 tok/s n=2 100.00% — 3
cloudflare-workers-ai 2884 ms 3889 ms 45 tok/s n=2 100.00% — 2
gmi 2991 ms 20736 ms 104 tok/s n=2 100.00% — 3
siliconflow 3021 ms 6095 ms 31 tok/s n=1 100.00% — 2
novita 3101 ms 3101 ms 23 tok/s n=2 100.00% — 1
phala 3147 ms 18611 ms 22 tok/s n=2 100.00% 1 provider_error 8
arcee 3763 ms 4584 ms 86 tok/s n=2 100.00% — 6
fireworks 4252 ms 4252 ms 67 tok/s n=1 100.00% — 1
featherless 5544 ms 13223 ms 42 tok/s n=2 100.00% — 3
deepinfra — — — 100.00% — 330
atlas-cloud — — 35 tok/s n=2 — — 0
baseten — — 71 tok/s n=1 — — 0
boundless — — 101 tok/s n=1 — — 0
chutes — — 20 tok/s n=1 0.00% — 2
io-net — — 94 tok/s n=2 — — 0
lyceum — — 145 tok/s n=1 — — 0
nebius — — 78 tok/s n=1 — — 0
venice — — 70 tok/s n=1 — — 0

Full provider & model leaderboard.

Provider diversity

28 routes.

More routes give the auto router more room to fail over around provider 429 and 5xx responses.

Streaming

Gateway overhead is measured separately.

Public status separates TLS/health overhead from full model latency so slow LLMs do not inflate the router metric.

Status

Metadata rollups.

Status samples store latency, outcome, provider, model, route, cost, and region metadata only.

Workspace access

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