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Moonshot AI vs Cohere
Kimi K3 is the most capable open-weight model for long coding runs. Cohere's Command models are smaller and aimed at private enterprise RAG.
By The Subconscious Team · Updated
Moonshot AI vs Cohere: key differences
Moonshot's Kimi K3 is a 2.8 trillion parameter mixture-of-experts model with a 1M context and native vision, and Vals AI scored it 93.4% on SWE-bench Verified, fourth overall. The hosted API costs $3 in and $15 out with cached input at $0.30. Cohere's Command A+ is a 218B model with 25B active and a 128K window, and Cohere says it trails the latest open models on agentic coding. Command A lists at $2.50 in and $10 out with 256K context. For repo-scale coding agents, Kimi K3 is the stronger model, though it always thinks and runs around 33 tokens per second.
Cohere wins on practicality. Self-hosting Kimi K3 takes a 64+ accelerator cluster, and its custom license adds a commercial agreement above $20M in hosting revenue. Command A+ runs on two H100s or one B200 in 4-bit form under Apache 2.0, and Cohere supports private VPC and on-prem installs with fine-tuning. Moonshot paused new API subscriptions after K3 demand overran its GPUs, while Cohere sells through Bedrock, Azure AI Foundry and OCI. Cohere also offers Embed 4 and Rerank 4. Choose Kimi K3 for hard coding, Cohere for manageable enterprise deployments.
What Moonshot AI and Cohere do
Moonshot AI
Moonshot AI is the Beijing lab behind the Kimi models. Its flagship Kimi K3 launched July 16, 2026 as a 2.8 trillion parameter mixture-of-experts model that activates 16 of 896 experts per token, with native vision and a 1M token context. It is the first open model in the 3T class, and full weights landed on Hugging Face on July 27. The hosted API costs $3 in and $15 out per million tokens, with cached input at $0.30, and it runs through an OpenAI-compatible endpoint, Kimi Code in the terminal, OpenRouter and Cloudflare Workers AI.
Example models: Kimi K3, Kimi K2.6
Full Moonshot AI profileCohere
Cohere is a Toronto-based lab that sells models and platforms to banks, governments and large enterprises rather than consumers. Its generative line is the Command family. Command A+, released May 20, 2026, is a 218B-parameter mixture-of-experts model with 25B active, published under Apache 2.0 with a 128K context window, and it combines reasoning, vision, translation and tool use in one set of weights. Command A has a 256K window and lists at $2.50 in and $10 out per million tokens, while Command R7B costs $0.0375 in. June 2026 added North Mini Code, a 30B Apache 2.0 coding model, and the lineup also includes Aya multilingual models and Transcribe for speech.
Example models: Command A+, Command A, Embed 4, Rerank 4
Full Cohere profileShould you choose Moonshot AI or Cohere?
Moonshot AI
Choose Moonshot AI for
- Long-horizon coding on huge repositories
- Near-frontier coding scores on open weights
- Document-heavy research with 1M context
Cohere
Choose Cohere for
- Self-hosting on two H100s
- Permissive Apache 2.0 licensing at any scale
- Enterprise RAG with reranking
Moonshot AI vs Cohere at a glance
| Attribute | Moonshot AI | Cohere |
|---|---|---|
| Model access | Open weights, custom license | Closed, plus open Command A+ |
| Flagship models | Kimi K3, Kimi K2.6 | Command A+, Command A, Embed 4, Rerank 4 |
| Speed | ~33 tok/s on Kimi K3 | 375 tok/s on Command A+ W4A4, per Cohere |
| Price | $3 in, $15 out (Kimi K3) | $0.0375–$2.50 in, $0.15–$10 out per 1M |
| Customization | Open weights to fine-tune | Enterprise fine-tuning, incl. private |
| Deployment | API, Kimi Code, OpenRouter | API, Bedrock, Azure, OCI, VPC, on-prem |
| Long context | 1M | 256K on Command A; 128K on A+ |
Frequently asked questions
What is the difference between Moonshot AI and Cohere?
Kimi K3 is the most capable open-weight model for long coding runs. Cohere's Command models are smaller and aimed at private enterprise RAG.
When should I choose Moonshot AI over Cohere?
Long-horizon coding on huge repositories; Near-frontier coding scores on open weights; Document-heavy research with 1M context.
When should I choose Cohere over Moonshot AI?
Self-hosting on two H100s; Permissive Apache 2.0 licensing at any scale; Enterprise RAG with reranking.
Is Moonshot AI or Cohere cheaper?
Moonshot AI: $3 in, $15 out (Kimi K3). Cohere: $0.0375–$2.50 in, $0.15–$10 out per 1M. The cheaper choice depends on the model and workload.
Which has more context, Moonshot AI or Cohere?
Moonshot AI: 1M. Cohere: 256K on Command A; 128K on A+.
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