Kimi K2 Instruct vs Seed-OSS-36B-Instruct vs Gemini 2.5 Flash
Gemini 2.5 Flash comes out ahead, 84 to 40 and 25 on our weighted score, and it is the cheaper option too.
Moonshot AIKimi K2 Instruct
25/100- ECI139.9
- Price$0.57 / $2.30
- Context131K
ByteDance SeedSeed-OSS-36B-Instruct
40/100- ECI—
- Price—
- Context524K
- Our pick
GoogleGemini 2.5 Flash
84/100- ECI140.6
- Price$0.30 / $2.50
- Context1.05M
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 84/100 against Seed-OSS-36B-Instruct (40) and Kimi K2 Instruct (25). It leads on inputs & features and 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 priceGemini 2.5 FlashGemini 2.5 Flash $0.85 · Kimi K2 Instruct $1.00 per 1M tokens (3:1 blend) · Seed-OSS-36B-Instruct unpriced
- Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · Seed-OSS-36B-Instruct 524,288 · Kimi K2 Instruct 131,072 tokens
- Widest inputsGemini 2.5 FlashKimi K2 Instruct: Text · Seed-OSS-36B-Instruct: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingKimi K2 Instruct and Seed-OSS-36B-InstructPublishes downloadable weights (Modified MIT and Apache 2.0)
| Measure | Weight | Kimi K2 Instruct | Seed-OSS-36B-Instruct | Gemini 2.5 Flash |
|---|---|---|---|---|
| Inputs & features | 60% | 25 | 35 | 100 |
| Context window | 40% | 25 | 49 | 61 |
| Overall | 100% | 25/100 | 40/100 | 84/100 |
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 | Kimi K2 InstructMoonshot AI | Seed-OSS-36B-InstructByteDance Seed | Gemini 2.5 FlashGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.9 | — | 140.6 (best) |
| ECI rank | #112 of 165 | — | #110 of 165 (best) |
| GPQA DiamondGraduate-level science questions | — | 71.5% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 67.5% | — |
| Price per million tokens | |||
| Input | $0.57 | — | $0.30 (best) |
| Output | $2.30 (best) | — | $2.50 |
| Cached input | — | — | $0.03 |
| Blended (3:1) | $1.00 | — | $0.85 (best) |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 11 providers | — | Official Google API |
| Limits | |||
| Context window | 131,072 tokens | 524,288 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 524,288 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenModified MIT | OpenApache 2.0 | Proprietary |
| API model ID | — | — | gemini-2.5-flash |
| API providers | 11 | — | 32 (best) |
| Released | Jul 11, 2025 | Aug 20, 2025 | Jun 17, 2025 |
| Knowledge cutoff | — | Jul 2024 | Jan 2025 |
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
- Seed-OSS-36B-Instruct—
- Gemini 2.5 Flash$8.00
Which should you choose?
Which is better: Kimi K2 Instruct, Seed-OSS-36B-Instruct or Gemini 2.5 Flash?
Gemini 2.5 Flash is the better all-round choice, scoring 84/100 against Seed-OSS-36B-Instruct (40) and Kimi K2 Instruct (25). It leads on inputs & features and 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, Kimi K2 Instruct, Seed-OSS-36B-Instruct or Gemini 2.5 Flash?
Gemini 2.5 Flash is cheaper at $0.30 input / $2.50 output per million tokens (official Google API price). 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 $0.85 per million tokens for Gemini 2.5 Flash versus $1.00 for Kimi K2 Instruct (1.2× 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. Kimi K2 Instruct has an ECI of 139.9, Seed-OSS-36B-Instruct has not been scored yet and Gemini 2.5 Flash has an ECI of 140.6.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K2 Instruct, Seed-OSS-36B-Instruct and Gemini 2.5 Flash 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?
Gemini 2.5 Flash has the largest context window at 1,048,576 tokens, against 524,288 for Seed-OSS-36B-Instruct and 131,072 for Kimi K2 Instruct. Maximum output per response: Kimi K2 Instruct up to 32,768, Seed-OSS-36B-Instruct up to 524,288, Gemini 2.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Kimi K2 Instruct accepts text; Seed-OSS-36B-Instruct accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
Kimi K2 Instruct and Seed-OSS-36B-Instruct publishes its weights (Modified MIT and Apache 2.0) and can be self-hosted; Gemini 2.5 Flash is proprietary.
Which is newer?
Seed-OSS-36B-Instruct is the newest, released Aug 20, 2025. Kimi K2 Instruct came out Jul 11, 2025; Gemini 2.5 Flash came out Jun 17, 2025. Knowledge cutoff: Seed-OSS-36B-Instruct Jul 2024, Gemini 2.5 Flash Jan 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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