Qwen3.5 27B vs Kimi K2 Thinking vs Seed 2.0 Code
Qwen3.5 27B comes out ahead, 61 to 57 and 42 on our weighted score, and it is the cheaper option too.
- Our pick
Alibaba (Qwen)Qwen3.5 27B
61/100- ECI—
- Price$0.30 / $2.40
- Context262K
Moonshot AIKimi K2 Thinking
42/100- ECI146.0
- Price$0.60 / $2.50
- Context262K
ByteDance SeedSeed 2.0 Code
57/100- ECI—
- Price$0.475 / $2.37
- Context262K
Qwen3.5 27B is our pick
Qwen3.5 27B is the better all-round choice, scoring 61/100 against Seed 2.0 Code (57) and Kimi K2 Thinking (42). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. 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 priceQwen3.5 27BQwen3.5 27B $0.825 · Seed 2.0 Code $0.95 · Kimi K2 Thinking $1.07 per 1M tokens (3:1 blend)
- Longest contextAbout the sameQwen3.5 27B 262,144 · Kimi K2 Thinking 262,144 · Seed 2.0 Code 262,144 tokens
- Widest inputsQwen3.5 27BQwen3.5 27B: Text, Images, Audio, Video · Kimi K2 Thinking: Text · Seed 2.0 Code: Text, Images, Video
- Self-hostingQwen3.5 27B and Kimi K2 ThinkingPublishes downloadable weights
| Measure | Weight | Qwen3.5 27B | Kimi K2 Thinking | Seed 2.0 Code |
|---|---|---|---|---|
| Price | 50% | 54 | 48 | 51 |
| Inputs & features | 30% | 90 | 35 | 80 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 61/100 | 42/100 | 57/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.5 27BAlibaba (Qwen) | Kimi K2 ThinkingMoonshot AI | Seed 2.0 CodeByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 146.0 | — |
| ECI rank | — | #72 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 84.2% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 83.1% | — |
| Price per million tokens | |||
| Input | $0.30 (best) | $0.60 | $0.475 |
| Output | $2.40 | $2.50 | $2.37 (best) |
| Cached input | — | — | $0.095 |
| Blended (3:1) | $0.825 (best) | $1.07 | $0.95 |
| Long-context rate | Same rate | Same rate | Over 32K: $0.712 / $3.56 |
| Price source | Official Alibaba API | Median of 10 providers | Official Volcengine Ark API |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 65,536 tokens | 262,144 tokens (best) | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yes | Yes | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | qwen3.5-27b | — | doubao-seed-2-0-code-preview-260215 |
| API providers | 16 (best) | 10 | 10 |
| Released | Feb 23, 2026 | Nov 6, 2025 | Feb 14, 2026 |
| Knowledge cutoff | — | Aug 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.5 27B$7.80
- Kimi K2 Thinking$11.00
- Seed 2.0 Code$9.50
Which should you choose?
Which is better: Qwen3.5 27B, Kimi K2 Thinking or Seed 2.0 Code?
Qwen3.5 27B is the better all-round choice, scoring 61/100 against Seed 2.0 Code (57) and Kimi K2 Thinking (42). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen3.5 27B, Kimi K2 Thinking or Seed 2.0 Code?
Qwen3.5 27B is cheaper at $0.30 input / $2.40 output per million tokens (official Alibaba API price). Seed 2.0 Code costs $0.475 input / $2.37 output per million tokens (official Volcengine Ark API price); Kimi K2 Thinking costs $0.60 input / $2.50 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.825 per million tokens for Qwen3.5 27B versus $0.95 for Seed 2.0 Code (1.2× as much) and $1.07 for Kimi K2 Thinking (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.5 27B has not been scored yet, Kimi K2 Thinking has an ECI of 146.0 and Seed 2.0 Code has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 27B, Kimi K2 Thinking and Seed 2.0 Code 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?
Qwen3.5 27B, Kimi K2 Thinking and Seed 2.0 Code share the same 262,144-token context window. Maximum output per response: Qwen3.5 27B up to 65,536, Kimi K2 Thinking up to 262,144, Seed 2.0 Code up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 27B accepts text, images, audio and video; Kimi K2 Thinking accepts text; Seed 2.0 Code accepts text, images and video. Qwen3.5 27B handles the widest range of inputs.
Are any of these open source?
Qwen3.5 27B and Kimi K2 Thinking publishes its weights and can be self-hosted; Seed 2.0 Code is proprietary.
Which is newer?
Qwen3.5 27B is the newest, released Feb 23, 2026. Seed 2.0 Code came out Feb 14, 2026; Kimi K2 Thinking came out Nov 6, 2025. Knowledge cutoff: Kimi K2 Thinking Aug 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 Oct 4, 2026.
