DeepSeek V3.2 vs Kimi K2.7-Code
DeepSeek V3.2 (2025) and Kimi K2.7-Code (2026) compare a standalone API model against a coding-specialized model. DeepSeek V3.2 ships a 160k-token context window, while Kimi K2.7-Code ships a 262k-token context window. On pricing, DeepSeek V3.2 costs $0.25/1M 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 V3.2 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 V3.2 | Kimi K2.7-Code |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 160k | 262k |
| Cheapest output | $0.38/1M tokens | $3.07/1M tokens |
| Provider routes | 7 tracked | 2 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- DeepSeek V3.2 has the lower cheapest tracked output price at $0.38/1M tokens.
- DeepSeek V3.2 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek V3.2 uniquely exposes Code execution in local model data.
- Local decision data tags DeepSeek V3.2 for Coding, RAG, and Agents.
- Kimi K2.7-Code has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2.7-Code uniquely exposes Vision, Multimodal, and Reasoning 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 V3.2
$296
Cheapest tracked route/tier: OpenRouter
Kimi K2.7-Code
$1,257
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $961. 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 $2.69/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Code execution before moving production traffic.
- Kimi K2.7-Code adds Vision, Multimodal, and Reasoning in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- DeepSeek V3.2 is $2.69/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- DeepSeek V3.2 adds Code execution in local capability data.
Specs
Pricing and availability
| Pricing attribute | DeepSeek V3.2 | Kimi K2.7-Code |
|---|---|---|
| Input price | $0.25/1M tokens | $0.61/1M tokens |
| Output price | $0.38/1M tokens | $3.07/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.2 | Kimi K2.7-Code |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on vision: Kimi K2.7-Code, multimodal input: Kimi K2.7-Code, reasoning mode: Kimi K2.7-Code, function calling: Kimi K2.7-Code, tool use: Kimi K2.7-Code, and code execution: DeepSeek V3.2. Both models share 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 V3.2 lists $0.25/1M input and $0.38/1M 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 V3.2 lower by about $1.06 per million blended tokens. Availability is 7 providers versus 2, so concentration risk also matters.
Choose DeepSeek V3.2 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose Kimi K2.7-Code when coding workflow support and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, DeepSeek V3.2 or Kimi K2.7-Code?
Kimi K2.7-Code supports 262k tokens, while DeepSeek V3.2 supports 160k 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 V3.2 or Kimi K2.7-Code?
DeepSeek V3.2 is cheaper on tracked token pricing. DeepSeek V3.2 costs $0.25/1M input and $0.38/1M 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 V3.2 or Kimi K2.7-Code open source?
DeepSeek V3.2 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 V3.2 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 V3.2 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 V3.2 and Kimi K2.7-Code?
DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, OpenRouter, and Microsoft Foundry. Kimi K2.7-Code is available on Moonshot AI Kimi and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-25. Data sourced from public model cards and provider documentation.