Kimi K3.1 Pro
kimi-k3-1-prokimi-k3.1-pro- 🎯 Moonshot AI's flagship open-weight multimodal reasoning model
- 📏 Massive 1M-token context window
- 👁️ Vision input plus deep reasoning traces
- 🔧 Function calling and web search for agentic workflows
- 💻 Tuned for long-horizon coding, CAD code, and financial research
- 🌍 Open weights from Moonshot AI
Moonshot is an AI research lab known for developing the Kimi family of large language models. The organization has gained recognition for building capable reasoning-oriented models, with the Kimi line representing its flagship series of text generation systems.
Explore 8 more models by Moonshot →Kimi K3.1 Pro sits at the top of Moonshot AI's open-weight lineup, a post-trained refinement of Kimi K3 that pairs multimodal input with extended reasoning and a one-million-token context window. Released in October 2026, it targets the hardest end of the assistant spectrum: tasks that unfold over many steps, span entire repositories or document sets, and require the model to call tools and search the web rather than answer from memory alone.
Within Moonshot's catalogue, the K-series splits by purpose. Kimi K3 Fast and K3.1 Pro Highspeed prioritise throughput, Kimi K2.7 Code is the coding-specialised branch, and the K2.x line covers general-purpose work. The Pro tier is the reasoning-heavy option, trading latency for depth on problems where a wrong first step is expensive.
Moonshot highlights long-horizon coding, agentic orchestration, financial research, and 3D modelling through generated CAD code as the model's core strengths. It is a strong fit for developers building autonomous agents, teams analysing very large document corpora, and anyone who needs a single model to read images, reason at length, and drive external tools in one session.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Routing | Input $/M | Cached $/M | Output $/M | Categories | API |
|---|---|---|---|---|---|---|---|
| ZLKPro-Api 0x0b0b…f446 | 82.28 | #3 | $0.067 | $0.0335 | $0.694 | newest, agent, chat | openai-chat-completions |
| Venice.ai Proxy 0x1f22…18c9 | 77.87 | #6 | $1.50 | $0.15 | $7.50 | chat, reasoning, coding | openai-chat-completions |
| ▲ Apex Ant 0x73b4…e736 | 72.15 | #7 | $1.875 | $0.19 | $9.375 | chat, premium | openai-chat-completions |
| Super Seeder 0xd19f…41f3 | 71.78 | #8 | $4.6876 | $0.4688 | $23.4379 | chat, coding, reasoning | openai-chat-completions |
| 💬 Banter 0x4122…e194 | 71.57 | #5 | $1.39 | $0.139 | $6.95 | — | openai-chat-completions |
| Edith AI 0xb269…b1a6 | 70.59 | #4 | $0.594 | $0.0594 | $2.97 | chat, coding | openai-chat-completions |
| Best 0x472f…69fd | 70.56 | #1 | $0.12 | $0.042 | $0.55 | chat, coding, agent | openai-chat-completions |
| attacompute.ai 0xd5e7…7be0 | 64.17 | #2 | $0.12 | $0.12 | $0.55 | chat, coding, reasoning | openai-chat-completions |
| Hana Gateway ✅ 0x4ae1…117b | 59.63 | gated | $0.08 | $0.02 | $1.00 | chat, coding, reasoning | openai-chat-completions |
| OpenCheap 0x0ee1…6c41 | 59.51 | gated | $0.3416 | $0.0342 | $1.7079 | chat, coding | openai-chat-completions |
| bartly.eth64.de 0x666e…4666 | 52.01 | gated | $0.3486 | $0.0349 | $1.7428 | chat, coding, reasoning | openai-chat-completions |
| Fire Ant 🔥🐜 0xbe05…bc5d | 50.00 | gated | $3.375 | $0.3375 | $16.875 | agent, chat, coding | — |
| JOI SEED 0x808a…6a8b | 47.49 | gated | $1.22 | $1.22 | $6.10 | chat, reasoning, vision | openai-chat-completions |
| antseed-cosmic-gecko-c46d 0xd9c0…c46d | 41.11 | gated | $0.08 | $0.056 | $0.24 | chat, coding | openai-chat-completions |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = buyer trust score (0-100, the AntSeed SDK's own formula). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.