DeepSeek-R1 vs Seed-OSS-36B-Instruct vs Kimi K2 Instruct
Seed-OSS-36B-Instruct comes out ahead, 40 to 31 and 25 on our weighted score.
DeepSeekDeepSeek-R1
31/100- ECI138.8
- Price$0.70 / $4.88
- Context128K
- Our pick
ByteDance SeedSeed-OSS-36B-Instruct
40/100- ECI—
- Price—
- Context524K
Moonshot AIKimi K2 Instruct
25/100- ECI139.9
- Price$0.57 / $2.30
- Context131K
Seed-OSS-36B-Instruct is our pick
Seed-OSS-36B-Instruct is the better all-round choice, scoring 40/100 against DeepSeek-R1 (31) and Kimi K2 Instruct (25). It leads on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceKimi K2 InstructKimi K2 Instruct $1.00 · DeepSeek-R1 $1.75 per 1M tokens (3:1 blend) · Seed-OSS-36B-Instruct unpriced
- Longest contextSeed-OSS-36B-InstructSeed-OSS-36B-Instruct 524,288 · Kimi K2 Instruct 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputsDeepSeek-R1: Text · Seed-OSS-36B-Instruct: Text · Kimi K2 Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-R1 | Seed-OSS-36B-Instruct | Kimi K2 Instruct |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 35 | 25 |
| Context window | 40% | 24 | 49 | 25 |
| Overall | 100% | 31/100 | 40/100 | 25/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1DeepSeek | Seed-OSS-36B-InstructByteDance Seed | Kimi K2 InstructMoonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.8 | — | 139.9 (best) |
| ECI rank | #119 of 165 | — | #112 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 71.7% (best) | 71.5% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% | 67.5% (best) | — |
| Price per million tokens | |||
| Input | $0.70 | — | $0.57 (best) |
| Output | $4.88 | — | $2.30 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $1.75 | — | $1.00 (best) |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 11 providers | — | Median of 11 providers |
| Limits | |||
| Context window | 128,000 tokens | 524,288 tokens (best) | 131,072 tokens |
| Max output | 32,768 tokens | 524,288 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | OpenModified MIT |
| API model ID | — | — | — |
| API providers | 12 (best) | — | 11 |
| Released | Jan 20, 2025 | Aug 20, 2025 | Jul 11, 2025 |
| Knowledge cutoff | Jul 2024 | Jul 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek-R1$16.76
- Seed-OSS-36B-Instruct—
- Kimi K2 Instruct$10.30
Which should you choose?
Which is better: DeepSeek-R1, Seed-OSS-36B-Instruct or Kimi K2 Instruct?
Seed-OSS-36B-Instruct is the better all-round choice, scoring 40/100 against DeepSeek-R1 (31) and Kimi K2 Instruct (25). It leads on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DeepSeek-R1, Seed-OSS-36B-Instruct or Kimi K2 Instruct?
Kimi K2 Instruct is cheaper at $0.57 input / $2.30 output per million tokens (median across 11 API providers). DeepSeek-R1 costs $0.70 input / $4.88 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for Kimi K2 Instruct versus $1.75 for DeepSeek-R1 (1.7× as much). Seed-OSS-36B-Instruct has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek-R1 has an ECI of 138.8, Seed-OSS-36B-Instruct has not been scored yet and Kimi K2 Instruct has an ECI of 139.9.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1, Seed-OSS-36B-Instruct and Kimi K2 Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Seed-OSS-36B-Instruct has the largest context window at 524,288 tokens, against 131,072 for Kimi K2 Instruct and 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, Seed-OSS-36B-Instruct up to 524,288, Kimi K2 Instruct up to 32,768 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; Seed-OSS-36B-Instruct accepts text; Kimi K2 Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0 and Modified MIT), so you can self-host them.
Which is newer?
Seed-OSS-36B-Instruct is the newest, released Aug 20, 2025. Kimi K2 Instruct came out Jul 11, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, Seed-OSS-36B-Instruct Jul 2024.
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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