Kimi K3.1 Pro
Moonshot
- 컨텍스트 창
- 1M 1,048,576 토큰
- 입력 / 출력
- 이미지, 텍스트, 동영상 → 텍스트
API 요금
USD / 토큰 100만 개
| 입력 | 출력 | 캐시 입력 |
|---|---|---|
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타임라인
- · 가중치 버전 · 근거 링크
입력/출력 가격 · USD / 토큰 100만 개
| 모델 | 근거 링크 | 입력/출력 가격 |
|---|---|---|
moonshotai/kimi-k3.1-prostandard | openrouter | $2.00 / $10.00 |
moonshotai/kimi-k3.1-pro:batchbatch | openrouter | $0.70 / $6.00 |
moonshotai/kimi-k3.1-prostandard | vercel-gateway | $2.00 / $10.00 |
kimi-k3.1-prostandard · 텍스트 | opencode-go | $2.00 / $10.00 |
- · 근거 링크 · GitHub search · Moonshot · commits · renj-arch/dimsred · @github-actions[bot]
발췌
Kimi K3.1 Pro is NOT callable. build.nvidia.com publishes the model, but its
- · 근거 링크 · GitHub search · Moonshot · commits · renj-arch/dimsred · @github-actions[bot]
- · 근거 링크 · GitHub search · Moonshot · commits · cmyolo441-coder/py.test · @claude
- · 근거 링크 · GitHub search · Moonshot · commits · MadAppGang/claudish · @erudenko
- · 근거 링크 · GitHub search · Moonshot · commits · DarkPrince922/Oreshnik · @claude
발췌
The form showed "Для Strix: openai/kimi-k3.1-pro" under a model with no such
- · 근거 링크 · GitHub search · Moonshot · pulls · zhao-wuyan/llm-info · @github-actions[bot]
- · 근거 링크 · GitHub search · Moonshot · pulls · vllm-project/vllm · @xaguilar-amd
발췌
- With Kimi-K3.1-Pro and the recipe's DSpark draft (`kv_cache_dtype: fp8`) on 8x MI325X, draft acceptance at 3 speculative tokens no longer collapses after a batch
- · 근거 링크 · GitHub search · Moonshot · pulls · vercel-labs/fx · @fazxes
발췌
- Kimi K3.1 Pro (`moonshotai/kimi-k3.1-pro`) is now a Token Pass model.
- · 근거 링크 · GitHub search · Moonshot · pulls · router-for-me/CLIProxyAPI · @evan188199-tech
발췌
feat(devin): add claude-fable-5-2 and kimi-k3-1-pro to default catalog
- · 근거 링크 · GitHub search · Moonshot · pulls · keithhchen/hatch · @keithhchen
발췌
Models: new `hatch_model_roles` roles `inspiration` and `content`, seeded `kimi-k3.1-pro`, resolved per session role.
- · 근거 링크 · GitHub search · Moonshot · pulls · keithhchen/hatch · @keithhchen
- · 근거 링크 · GitHub search · Moonshot · pulls · huggingface/speech-to-speech · @andimarafioti
발췌
Models: Qwen3.8-2.4T, Qwen3.8-27B, Gemma 4 31B, DeepSeek-V4.1-Flash, DeepSeek-V4-Pro, Kimi-K3.1-Pro, GLM-5.3, MiniMax-M3.1-Flash, Mistral-Large-4, Muse-Spark-Open, Nemotron-3.5-Super, Hy4-preview; small: LFM3-1.7B, Ling-3.0-tiny, granite-4.2-3b, granite-4.2-8b, Qwen3.5-9B, LFM2.5-24B, Nemotron-3.5-Lightning, Gemma 4
- · 근거 링크 · GitHub search · Moonshot · pulls · can1357/oh-my-pi · @will-bogusz
- · 근거 링크 · GitHub search · Moonshot · pulls · attilaolah/dotfiles · @renovate[bot]
발췌
[`bcb0152`](https://redirect.github.com/ggml-org/llama.cpp/commit/bcb015287) model: add Kimi-K3.1-Pro text model ([#​31779](https://redirect.github.com/ggml-org/llama.cpp/issues/31779))
- · 근거 링크 · GitHub search · Moonshot · pulls · adiudiuu/tps · @adiudiuu
- · 근거 링크 · GitHub search · Moonshot · pulls · adiudiuu/tps · @adiudiuu
- · 근거 링크 · GitHub search · Moonshot · pulls · Pinvou/CodeWhale · @asto18089
발췌
documents that missing field as HTTP 400. The `kimi-k3.1-pro[-highspeed]` direct-platform spellings did replay at default effort via the generic `kimi-` prefix heuristic, but were still
- · 근거 링크 · GitHub search · Moonshot · pulls · JavaZeroo/torchtitan · @JavaZeroo
발췌
| Kimi-K3.1-Pro attention shape (96 heads, 4096 tokens, top-k 2048), pairs, 1x H100 | first call about 7 s (compile), then 12 ms forward and
- · 근거 링크 · GitHub search · Moonshot · pulls · Heknon/AskCalls · @dependabot[bot]
발췌
<li>ai-sdk-provider: add kimi-k3-1-pro to known model ids by <a href="https://github.com/andrelandgraf"><code>@andrelandgraf</code></a> in <a href="https://redirect.github.com/neondatabase/neon-pkgs/pull/1091">neondatabase/neon-pkgs#1091</a></li>
- · 근거 링크 · GitHub search · Moonshot · pulls · Heknon/AskCalls · @dependabot[bot]
발췌
<li>ai-sdk-provider: add kimi-k3-1-pro to known model ids by <a href="https://github.com/andrelandgraf"><code>@andrelandgraf</code></a> in <a href="https://redirect.github.com/neondatabase/neon-pkgs/pull/1091">neondatabase/neon-pkgs#1091</a></li>
- · 근거 링크 · GitHub search · Moonshot · commits · Nulluminati/pi-extensions · @Nulluminati
- · 근거 링크 · GitHub search · Moonshot · pulls · lightseekorg/tokenspeed · @Yu-Zhewen
발췌
Kimi-K3.1-Pro on 8x MI355X (TP8, KVP8, FP8 KV cache, 3 DSpark drafts, the gfx950 stack through #3355), InferenceX's acceptance-length gate: SPEED-Bench coding prompts, 80 requests
- · 근거 링크 · GitHub search · Moonshot · pulls · lidge-jun/opencodex · @andrew05060414
발췌
rows showed prices. `cn:deepseek-v4.1-flash` came from OpenRouter (0.3/1.2). `cn:kimi-k3.1-pro`, `cn:glm-5.3-flash`, `zd/gpt-6-sol` and `zd/gemini-4-argon` came from models.dev.
- · 근거 링크 · GitHub search · Moonshot · pulls · anomalyco/models.dev · @models-dev-automation[bot]
발췌
- created: `/home/runner/_work/models.dev/models.dev/providers/requesty/models/kimi-k3.1-pro@eu.toml`
근거 링크
- · 카탈로그 등록 · Moonshot API ·
kimi-k3.1-pro
시그널 4
사양
Kimi K3.1 Pro: Moonshot의 AI 모델, 가중치 공개, 출시일 2026-10-23. 컨텍스트 윈도는 1,048,576 토큰입니다. 토큰 100만 개당 요금은 입력 $2.00, 출력 $10.00입니다.
- 컨텍스트 창
- 1,048,576
- 입력
- 이미지 · 텍스트 · 동영상
- 출력
- 텍스트
- 가중치
- 공개
- 입력 · USD / 토큰 100만 개
- $2.00
- 출력 · USD / 토큰 100만 개
- $10.00
- 캐시 입력 · USD / 토큰 100만 개
- $0.20
자주 묻는 질문
Kimi K3.1 Pro의 컨텍스트 창 크기는 얼마인가요?
컨텍스트 윈도는 1,048,576 토큰입니다.
Kimi K3.1 Pro의 가격은 얼마인가요?
토큰 100만 개당 요금은 입력 $2.00, 출력 $10.00입니다. 캐시 입력은 100만 개당 $0.20입니다.
Kimi K3.1 Pro의 가중치는 공개되어 있나요?
네. Moonshot에서 가중치를 공개합니다.
Kimi K3.1 Pro의 출시일은 언제인가요?
2026-10-23.