DeepSeek-V3.1 vs Kimi K2 Instruct
DeepSeek-V3.1 comes out ahead, 56 to 50 on our weighted score, and it is the cheaper option too.
- Our pick
DeepSeekDeepSeek-V3.1
56/100- ECI139.8
- Price$0.27 / $1.00
- Context131K
Moonshot AIKimi K2 Instruct
50/100- ECI139.9
- Price$0.57 / $2.30
- Context131K
Add a model
Make it a three-way comparison.
DeepSeek-V3.1 is our pick
DeepSeek-V3.1 is the better all-round choice, scoring 56/100 against Kimi K2 Instruct (50). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K2 InstructCapabilities Index (ECI): Kimi K2 Instruct 139.9 · DeepSeek-V3.1 139.8
- Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.453 · Kimi K2 Instruct $1.00 per 1M tokens (3:1 blend)
- Longest contextAbout the sameDeepSeek-V3.1 131,072 · Kimi K2 Instruct 131,072 tokens
- Widest inputsSame inputsDeepSeek-V3.1: Text · Kimi K2 Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-V3.1 | Kimi K2 Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 64 |
| Price | 25% | 63 | 48 |
| Inputs & features | 15% | 35 | 25 |
| Context window | 10% | 25 | 25 |
| Overall | 100% | 56/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-V3.1DeepSeek | Kimi K2 InstructMoonshot AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 139.8 | 139.9 (best) |
| ECI rank | #113 of 165 | #112 of 165 (best) |
| Price per million tokens | ||
| Input | $0.27 (best) | $0.57 |
| Output | $1.00 (best) | $2.30 |
| Cached input | — | — |
| Blended (3:1) | $0.453 (best) | $1.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 19 providers | Median of 11 providers |
| Limits | ||
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 32,768 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenMIT License | OpenModified MIT |
| API model ID | — | — |
| API providers | 19 (best) | 11 |
| Released | Aug 21, 2025 | Jul 11, 2025 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek-V3.1$4.70
- Kimi K2 Instruct$10.30
Which should you choose?
Which is better: DeepSeek-V3.1 or Kimi K2 Instruct?
DeepSeek-V3.1 is the better all-round choice, scoring 56/100 against Kimi K2 Instruct (50). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-V3.1 or Kimi K2 Instruct?
DeepSeek-V3.1 is cheaper at $0.27 input / $1.00 output per million tokens (median across 19 API providers). Kimi K2 Instruct costs $0.57 input / $2.30 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.453 per million tokens for DeepSeek-V3.1 versus $1.00 for Kimi K2 Instruct (2.2× as much).
Which scores higher on benchmarks?
Kimi K2 Instruct scores higher on the Capabilities Index (ECI): Kimi K2 Instruct 139.9 (#112 of 165) and DeepSeek-V3.1 139.8 (#113 of 165). The confidence ranges of the top two overlap (136.3–141.6 vs 135.6–143.2), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-V3.1 and Kimi K2 Instruct yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
DeepSeek-V3.1 and Kimi K2 Instruct share the same 131,072-token context window. Maximum output per response: DeepSeek-V3.1 up to 8,192, Kimi K2 Instruct up to 32,768 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-V3.1 accepts text; Kimi K2 Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (MIT License and Modified MIT), so you can self-host them.
Which is newer?
DeepSeek-V3.1 is the newest, released Aug 21, 2025. Kimi K2 Instruct came out Jul 11, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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