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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
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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 1694 ms 1837 ms 122 tok/s n=2 60.00% — 10
relace 1834 ms 8072 ms 100 tok/s n=2 100.00% — 15
together 838 ms 4545 ms 35 tok/s n=2 100.00% — 2
tinfoil 996 ms 1117 ms 76 tok/s n=2 100.00% — 2
telnyx 1052 ms 1052 ms 139 tok/s n=2 100.00% — 1
engy 1272 ms 2159 ms 59 tok/s n=2 100.00% — 8
boundless 1332 ms 1332 ms 105 tok/s n=2 100.00% — 1
featherless 1449 ms 1449 ms 42 tok/s n=2 100.00% — 1
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% — 7
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
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
gmi 3118 ms 20736 ms 104 tok/s n=2 100.00% — 3
fireworks 3249 ms 4252 ms 56 tok/s n=2 100.00% — 2
phala 3483 ms 18611 ms 22 tok/s n=2 100.00% 1 provider_error 9
arcee 3763 ms 4584 ms 86 tok/s n=2 100.00% — 6
kimi 8141 ms 10194 ms — 100.00% — 7
deepinfra — — — 100.00% — 308
atlas-cloud — — 35 tok/s n=2 — — 0
baseten — — 61 tok/s n=2 — — 0
chutes — — 20 tok/s n=1 0.00% — 2
io-net — — 94 tok/s n=2 — — 0
lyceum — — 183 tok/s n=2 — — 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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