DeepSeek V3 0324 vs Kimi K2.5
DeepSeek V3 0324 (2025) and Kimi K2.5 (2026) compare a standalone API model against a coding-specialized model. DeepSeek V3 0324 ships a 160k-token context window, while Kimi K2.5 ships a 256k-token context window. On SWE-bench Verified, DeepSeek V3 0324 and Kimi K2.5 are tied at 76.8. On pricing, DeepSeek V3 0324 costs $0.27/1M input tokens versus $0.44/1M 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 0324 is standalone API model, while Kimi K2.5 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 0324 | Kimi K2.5 |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, Agents, and Long context | Coding, RAG, and Agents |
| Context window | 160k | 256k |
| Cheapest output | $1.12/1M tokens | $2/1M tokens |
| Provider routes | 3 tracked | 10 tracked |
| Shared benchmarks | 2 rows | Google-Proof Q&A leader |
Decision tradeoffs
- DeepSeek V3 0324 has the lower cheapest tracked output price at $1.12/1M tokens.
- Local decision data tags DeepSeek V3 0324 for Coding, Agents, and Long context.
- Kimi K2.5 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 0.3 points.
- Kimi K2.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2.5 has broader tracked provider coverage for fallback and procurement flexibility.
- Kimi K2.5 uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Kimi K2.5 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 0324
$496
Cheapest tracked route/tier: Novita AI
Kimi K2.5
$852
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $356. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI, Microsoft Foundry, and Novita AI; start route-level A/B tests there.
- Kimi K2.5 is $0.88/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Kimi K2.5 adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on Fireworks AI, Microsoft Foundry, and Novita AI; start route-level A/B tests there.
- DeepSeek V3 0324 is $0.88/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-24 | 2026-03-15 |
| Context window | 160k | 256k |
| Parameters | 671B | 1T (MoE, 384 experts) |
| Architecture | decoder only | mixture of experts |
| License | MIT(OSI) | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V3 0324 | Kimi K2.5 |
|---|---|---|
| Input price | $0.27/1M tokens | $0.44/1M tokens |
| Output price | $1.12/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3 0324 | Kimi K2.5 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V3 0324 | Kimi K2.5 |
|---|---|---|
| SWE-bench Verified | 76.8 | 76.8 |
| Google-Proof Q&A | 87.6 | 87.9 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has DeepSeek V3 0324 and Kimi K2.5 tied at 76.8; Google-Proof Q&A has DeepSeek V3 0324 at 87.6 and Kimi K2.5 at 87.9, with Kimi K2.5 ahead by 0.3 points. The largest visible gap is 0.3 points on Google-Proof Q&A, 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 K2.5, multimodal input: Kimi K2.5, function calling: Kimi K2.5, and structured outputs: Kimi K2.5. Both models share the core language-model surface, 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 0324 lists $0.27/1M input and $1.12/1M output tokens on the cheapest tracked provider, while Kimi K2.5 lists $0.44/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3 0324 lower by about $0.38 per million blended tokens. Availability is 3 providers versus 10, so concentration risk also matters.
Choose DeepSeek V3 0324 when provider fit and lower input-token cost are central to the workload. Choose Kimi K2.5 when coding workflow support, larger context windows, and broader provider choice 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 V3 0324 or Kimi K2.5?
Kimi K2.5 supports 256k tokens, while DeepSeek V3 0324 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 0324 or Kimi K2.5?
DeepSeek V3 0324 is cheaper on tracked token pricing. DeepSeek V3 0324 costs $0.27/1M input and $1.12/1M output tokens. Kimi K2.5 costs $0.44/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3 0324 or Kimi K2.5 open source?
DeepSeek V3 0324 is listed under MIT. Kimi K2.5 is listed under Proprietary. 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 0324 or Kimi K2.5?
Kimi K2.5 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 0324 or Kimi K2.5?
Kimi K2.5 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 0324 and Kimi K2.5?
DeepSeek V3 0324 is available on Fireworks AI, Microsoft Foundry, and Novita AI. Kimi K2.5 is available on Cloudflare Workers AI, Fireworks AI, OpenRouter, Together AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.