DeepSeek V4 Pro vs Kimi K2.7-Code
DeepSeek V4 Pro (2026) and Kimi K2.7-Code (2026) compare a standalone API model against a coding-specialized model. DeepSeek V4 Pro ships a 1m-token context window, while Kimi K2.7-Code ships a 262k-token context window. On MCP-Atlas, Kimi K2.7-Code leads by 6.6 pts. On pricing, DeepSeek V4 Pro costs $0.43/1M input tokens versus $0.61/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: DeepSeek V4 Pro is standalone API model, while Kimi K2.7-Code is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Pro | Kimi K2.7-Code |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 262k |
| Cheapest output | $0.87/1M tokens | $3.07/1M tokens |
| Provider routes | 5 tracked | 2 tracked |
| Shared benchmarks | 2 shared | MCP-Atlas leader |
Decision tradeoffs
- DeepSeek V4 Pro holds a shared-benchmark lead on GeneBench-Pro, ahead by 0.1 points.
- DeepSeek V4 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V4 Pro has the lower cheapest tracked output price at $0.87/1M tokens.
- DeepSeek V4 Pro has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags DeepSeek V4 Pro for Coding, RAG, and Agents.
- Kimi K2.7-Code holds a shared-benchmark lead on MCP-Atlas, ahead by 6.6 points.
- Kimi K2.7-Code uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Kimi K2.7-Code for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V4 Pro
$566
Cheapest tracked route/tier: DeepSeek Platform
Kimi K2.7-Code
$1,257
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $691. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Kimi K2.7-Code is $2.20/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Kimi K2.7-Code adds Vision and Multimodal in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- DeepSeek V4 Pro is $2.20/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2026-06-12 |
| Context window | 1m | 262k |
| Parameters | 1.6T | 1T |
| Architecture | Mixture of Experts | Mixture of Experts |
| License | MITOSI-approved | MITOSI-approved |
| Openness | Open source | Open source |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V4 Pro | Kimi K2.7-Code |
|---|---|---|
| Input price | $0.43/1M tokens | $0.61/1M tokens |
| Output price | $0.87/1M tokens | $3.07/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V4 Pro | Kimi K2.7-Code |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V4 Pro | Kimi K2.7-Code |
|---|---|---|
| MCP-Atlas | 69.4 | 76.0 |
| GeneBench-Pro | 2.4 | 2.3 |
Deep dive
On shared benchmark coverage, MCP-Atlas has DeepSeek V4 Pro at 69.4 and Kimi K2.7-Code at 76, with Kimi K2.7-Code ahead by 6.6 points; GeneBench-Pro has DeepSeek V4 Pro at 2.4 and Kimi K2.7-Code at 2.3, with DeepSeek V4 Pro ahead by 0.1 points. The largest visible gap is 6.6 points on MCP-Atlas, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Kimi K2.7-Code and multimodal input: Kimi K2.7-Code. Both models share reasoning mode, function calling, tool use, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, DeepSeek V4 Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider, while Kimi K2.7-Code lists $0.61/1M input and $3.07/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V4 Pro lower by about $0.78 per million blended tokens. Availability is 5 providers versus 2, so concentration risk also matters.
Choose DeepSeek V4 Pro when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Kimi K2.7-Code when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, DeepSeek V4 Pro or Kimi K2.7-Code?
DeepSeek V4 Pro supports 1m tokens, while Kimi K2.7-Code supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V4 Pro or Kimi K2.7-Code?
DeepSeek V4 Pro is cheaper on tracked token pricing. DeepSeek V4 Pro costs $0.43/1M input and $0.87/1M output tokens. Kimi K2.7-Code costs $0.61/1M input and $3.07/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V4 Pro or Kimi K2.7-Code open source?
DeepSeek V4 Pro is listed under MIT. Kimi K2.7-Code is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, DeepSeek V4 Pro or Kimi K2.7-Code?
Kimi K2.7-Code has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, DeepSeek V4 Pro or Kimi K2.7-Code?
Kimi K2.7-Code has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek V4 Pro and Kimi K2.7-Code?
DeepSeek V4 Pro is available on DeepSeek Platform, Fireworks AI, OpenRouter, Vercel AI Gateway, and Novita AI. Kimi K2.7-Code is available on Moonshot AI Kimi and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.