Qwen3.5 27B vs Gemma 4 31B IT vs Seed 2.0 Code
Gemma 4 31B IT comes out ahead, 70 to 61 and 57 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3.5 27B
61/100- ECI—
- Price$0.30 / $2.40
- Context262K
- Our pick
GoogleGemma 4 31B IT
70/100- ECI142.8
- Price$0.14 / $0.40
- Context262K
ByteDance SeedSeed 2.0 Code
57/100- ECI—
- Price$0.475 / $2.37
- Context262K
Gemma 4 31B IT is our pick
Gemma 4 31B IT is the better all-round choice, scoring 70/100 against Qwen3.5 27B (61) and Seed 2.0 Code (57). It leads on price. Qwen3.5 27B wins on 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 priceGemma 4 31B ITGemma 4 31B IT $0.205 · Qwen3.5 27B $0.825 · Seed 2.0 Code $0.95 per 1M tokens (3:1 blend)
- Longest contextAbout the sameQwen3.5 27B 262,144 · Gemma 4 31B IT 262,144 · Seed 2.0 Code 262,144 tokens
- Widest inputsQwen3.5 27BQwen3.5 27B: Text, Images, Audio, Video · Gemma 4 31B IT: Text, Images · Seed 2.0 Code: Text, Images, Video
- Self-hostingQwen3.5 27B and Gemma 4 31B ITPublishes downloadable weights
| Measure | Weight | Qwen3.5 27B | Gemma 4 31B IT | Seed 2.0 Code |
|---|---|---|---|---|
| Price | 50% | 54 | 83 | 51 |
| Inputs & features | 30% | 90 | 70 | 80 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 61/100 | 70/100 | 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) | Gemma 4 31B ITGoogle | Seed 2.0 CodeByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 142.8 | — |
| ECI rank | — | #86 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 75.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 73.3% | — |
| SimpleQA VerifiedShort factual questions | — | 10.4% | — |
| Price per million tokens | |||
| Input | $0.30 | $0.14 (best) | $0.475 |
| Output | $2.40 | $0.40 (best) | $2.37 |
| Cached input | — | — | $0.095 |
| Blended (3:1) | $0.825 | $0.205 (best) | $0.95 |
| Long-context rate | Same rate | Same rate | Over 32K: $0.712 / $3.56 |
| Price source | Official Alibaba API | Median of 30 providers | Official Volcengine Ark API |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 65,536 tokens | 32,768 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | 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 | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | qwen3.5-27b | gemma-4-31b-it | doubao-seed-2-0-code-preview-260215 |
| API providers | 16 | 38 (best) | 10 |
| Released | Feb 23, 2026 | Apr 2, 2026 | Feb 14, 2026 |
| 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.
- Qwen3.5 27B$7.80
- Gemma 4 31B IT$2.20
- Seed 2.0 Code$9.50
Which should you choose?
Which is better: Qwen3.5 27B, Gemma 4 31B IT or Seed 2.0 Code?
Gemma 4 31B IT is the better all-round choice, scoring 70/100 against Qwen3.5 27B (61) and Seed 2.0 Code (57). It leads on price. Qwen3.5 27B wins on 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, Gemma 4 31B IT or Seed 2.0 Code?
Gemma 4 31B IT is cheaper at $0.14 input / $0.40 output per million tokens (median across 30 API providers). Qwen3.5 27B costs $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). At a typical mix of three input tokens to one output token, that is $0.205 per million tokens for Gemma 4 31B IT versus $0.825 for Qwen3.5 27B (4× as much) and $0.95 for Seed 2.0 Code (4.6× 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, Gemma 4 31B IT has an ECI of 142.8 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, Gemma 4 31B IT 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, Gemma 4 31B IT and Seed 2.0 Code share the same 262,144-token context window. Maximum output per response: Qwen3.5 27B up to 65,536, Gemma 4 31B IT up to 32,768, 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; Gemma 4 31B IT accepts text and images; 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 Gemma 4 31B IT publishes its weights and can be self-hosted; Seed 2.0 Code is proprietary.
Which is newer?
Gemma 4 31B IT is the newest, released Apr 2, 2026. Qwen3.5 27B came out Feb 23, 2026; Seed 2.0 Code came out Feb 14, 2026.
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.
