Kimi K2 Instruct vs DeepSeek R1 0528
DeepSeek R1 0528 comes out ahead, 53 to 50 on our weighted score, and it is the cheaper option too.
Moonshot AIKimi K2 Instruct
50/100- ECI139.9
- Price$0.57 / $2.30
- Context131K
- Our pick
DeepSeekDeepSeek R1 0528
53/100- ECI141.2
- Price$0.512 / $2.19
- Context164K
Add a model
Make it a three-way comparison.
DeepSeek R1 0528 is our pick
DeepSeek R1 0528 is the better all-round choice, scoring 53/100 against Kimi K2 Instruct (50). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek R1 0528Capabilities Index (ECI): DeepSeek R1 0528 141.2 · Kimi K2 Instruct 139.9
- Lowest priceDeepSeek R1 0528DeepSeek R1 0528 $0.932 · Kimi K2 Instruct $1.00 per 1M tokens (3:1 blend)
- Longest contextDeepSeek R1 0528DeepSeek R1 0528 163,840 · Kimi K2 Instruct 131,072 tokens
- Widest inputsSame inputsKimi K2 Instruct: Text · DeepSeek R1 0528: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Kimi K2 Instruct | DeepSeek R1 0528 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 66 |
| Price | 25% | 48 | 49 |
| Inputs & features | 15% | 25 | 35 |
| Context window | 10% | 25 | 28 |
| Overall | 100% | 50/100 | 53/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Kimi K2 InstructMoonshot AI | DeepSeek R1 0528DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 139.9 | 141.2 (best) |
| ECI rank | #112 of 165 | #108 of 165 (best) |
| GPQA DiamondGraduate-level science questions | — | 76.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 66.4% |
| Price per million tokens | ||
| Input | $0.57 | $0.512 (best) |
| Output | $2.30 | $2.19 (best) |
| Cached input | — | — |
| Blended (3:1) | $1.00 | $0.932 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 16 providers |
| Limits | ||
| Context window | 131,072 tokens | 163,840 tokens (best) |
| Max output | 32,768 tokens | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenModified MIT | OpenMIT |
| API model ID | — | — |
| API providers | 11 | 16 (best) |
| Released | Jul 11, 2025 | May 28, 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.
- Kimi K2 Instruct$10.30
- DeepSeek R1 0528$9.50
Which should you choose?
Which is better: Kimi K2 Instruct or DeepSeek R1 0528?
DeepSeek R1 0528 is the better all-round choice, scoring 53/100 against Kimi K2 Instruct (50). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Kimi K2 Instruct or DeepSeek R1 0528?
DeepSeek R1 0528 is cheaper at $0.512 input / $2.19 output per million tokens (median across 16 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 $0.932 per million tokens for DeepSeek R1 0528 versus $1.00 for Kimi K2 Instruct (1.1× as much).
Which scores higher on benchmarks?
DeepSeek R1 0528 scores higher on the Capabilities Index (ECI): DeepSeek R1 0528 141.2 (#108 of 165) and Kimi K2 Instruct 139.9 (#112 of 165). The confidence ranges of the top two overlap (139.0–142.9 vs 136.3–141.6), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K2 Instruct and DeepSeek R1 0528 yet, so there is no like-for-like coding score. On overall capability, DeepSeek R1 0528 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 R1 0528 has the largest context window at 163,840 tokens, against 131,072 for Kimi K2 Instruct. Maximum output per response: Kimi K2 Instruct up to 32,768, DeepSeek R1 0528 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Kimi K2 Instruct accepts text; DeepSeek R1 0528 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Modified MIT and MIT), so you can self-host them.
Which is newer?
Kimi K2 Instruct is the newest, released Jul 11, 2025. DeepSeek R1 0528 came out May 28, 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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