kimi-k2.6 API — compare providers

The same model (kimi-k2.6) is served by 17 providers; Baidu is the cheapest at $2.856/1M blended — the priciest (Phala) costs 99% more. On quality, kimi-k2.6 scores 1461 on the LMArena (Chatbot Arena) — so the cheapest endpoint is also the best value per dollar here.

LicenseModified MITopen weights · conditional · terms
Knowledge cutoffApril 2026source · ranked
Quality (Elo)1461LMArena (Chatbot Arena) · source
Intelligence45.1Artificial Analysis Intelligence Index · source · ranked

Quality and intelligence scores are attached to the model itself — identical whichever provider serves it. Verified 2026-09-04.

RankProviderInput /1MOutput /1MBlended /1MValue (Elo/$)
1Baidu$0.5482$2.308$2.856 ← cheapest512 ← best value
2Chutes$0.58$3.4$3.98367
3CoreWeave$0.65$3.41$4.06360
4SiliconFlow$0.77$3.4$4.17350
5Novita AI$0.8$3.4$4.2348
6Crusoe$0.7$3.5$4.2348
7DeepInfra$0.75$3.5$4.25344
8Venice$0.75$3.5$4.25344
9Parasail$0.75$3.5$4.25344
10GMICloud$0.855$3.6$4.455328
11Fireworks AI$0.95$4$4.95295
12DigitalOcean$0.95$4$4.95295
13AtlasCloud$0.95$4$4.95295
14Cloudflare$0.95$4$4.95295
15Moonshot AI$0.95$4$4.95295
16BaseTen$0.95$4$4.95295
17Phala$1.09$4.6$5.69257

Value = model Elo ÷ blended price per 1M tokens. Since the model's quality is identical across providers, the cheapest endpoint is also the best value per dollar.

Prices are per 1M tokens (USD). "Blended" = input + output, for coarse ranking. Same underlying model, 17 serving providers, 99% spread top to bottom. Context window: 262,144 tokens (235,929 max output) — see how it ranks in biggest context windows. See how this compares across the catalogue in same model, different price, or find the best quality per dollar in the value ranking.

Cost per 1,000 requests by workload

What each provider actually bills for a representative job, not just the sticker price.

ProviderChatbot
1000 in / 500 out
RAG / long context
8000 in / 500 out
Batch summarize
4000 in / 1000 out
Baidu$1.70$5.54$4.50
Chutes$2.28$6.34$5.72
CoreWeave$2.35$6.90$6.01
SiliconFlow$2.47$7.86$6.48
Novita AI$2.50$8.10$6.60
Crusoe$2.45$7.35$6.30
DeepInfra$2.50$7.75$6.50
Venice$2.50$7.75$6.50
Parasail$2.50$7.75$6.50
GMICloud$2.65$8.64$7.02
Fireworks AI$2.95$9.60$7.80
DigitalOcean$2.95$9.60$7.80
AtlasCloud$2.95$9.60$7.80
Cloudflare$2.95$9.60$7.80
Moonshot AI$2.95$9.60$7.80
BaseTen$2.95$9.60$7.80
Phala$3.39$11.02$8.96

Estimate your own workload

Input tokens/request:   Output tokens/request:   Requests:

ProviderEstimated cost (USD)

Self-host / quantized builds

Open weights under Modified MIT — you can run kimi-k2.6 on your own hardware instead of paying per token. Quantized builds lower the memory footprint; whether it fits your GPU or Mac depends on the model's size. Formats: GGUF for llama.cpp / Ollama / LM Studio, AWQ and GPTQ for GPU serving, MLX for Apple silicon.

Links search the live model hubs (Hugging Face, Ollama) so they track new builds as they appear — we don't host weights. Which formats exist depends on what the model owner and community have published.