Gemma 4 31B IT vs Gemma 4 E2B IT vs Qwen3.5 Flash
Too close to call on our weighted score (Gemma 4 E2B IT 79, Qwen3.5 Flash 79, Gemma 4 31B IT 70). The right pick depends on what you value most.
Google
Gemma 4 31B IT
70/100- ECI142.8
- Price$0.14 / $0.40
- Context262K
Google
Gemma 4 E2B IT
79/100- ECI—
- Price$0.07 / $0.09
- Context131K
Alibaba (Qwen)
Qwen3.5 Flash
79/100- ECI144.0
- Price$0.10 / $0.40
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (Gemma 4 E2B IT 79/100, Qwen3.5 Flash 79/100, Gemma 4 31B IT 70/100), so choose by what matters most for your work: Gemma 4 E2B IT on price and Qwen3.5 Flash for long inputs. 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 E2B ITGemma 4 E2B IT $0.075 · Qwen3.5 Flash $0.175 · Gemma 4 31B IT $0.205 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 FlashQwen3.5 Flash 1,000,000 · Gemma 4 31B IT 262,144 · Gemma 4 E2B IT 131,072 tokens
- Widest inputsGemma 4 E2B IT and Qwen3.5 FlashGemma 4 31B IT: Text, Images · Gemma 4 E2B IT: Text, Images, Audio · Qwen3.5 Flash: Text, Images, Video
- Self-hostingGemma 4 31B IT and Gemma 4 E2B ITPublishes downloadable weights
| Measure | Weight | Gemma 4 31B IT | Gemma 4 E2B IT | Qwen3.5 Flash |
|---|---|---|---|---|
| Price | 50% | 83 | 100 | 86 |
| Inputs & features | 30% | 70 | 80 | 80 |
| Context window | 20% | 37 | 24 | 60 |
| Overall | 100% | 70/100 | 79/100 | 79/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 142.8 | — | 144.0 (best) |
| ECI rank | #86 of 148 | — | #82 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 75.8% | — | 82.3% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 18.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 73.3% | — | 84.4% (best) |
| SimpleQA VerifiedShort factual questions | 10.4% | — | 20.3% (best) |
| Price per million tokens | |||
| Input | $0.14 | $0.07 (best) | $0.10 |
| Output | $0.40 | $0.09 (best) | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.205 | $0.075 (best) | $0.175 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 30 providers | Median of 2 providers | Official Alibaba API |
| Limits | |||
| Context window | 262,144 tokens | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 32,768 tokens | 8,192 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | gemma-4-31b-it | — | qwen3.5-flash |
| API providers | 38 (best) | 2 | 8 |
| Released | Apr 2, 2026 | Apr 2, 2026 | Feb 23, 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.
Gemma 4 31B IT$2.20
Gemma 4 E2B IT$0.88
Qwen3.5 Flash$1.80
Which should you choose?
Which is better: Gemma 4 31B IT, Gemma 4 E2B IT or Qwen3.5 Flash?
It is close. Our weighted score puts them within a point (Gemma 4 E2B IT 79/100, Qwen3.5 Flash 79/100, Gemma 4 31B IT 70/100), so choose by what matters most for your work: Gemma 4 E2B IT on price and Qwen3.5 Flash for long inputs. 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, Gemma 4 31B IT, Gemma 4 E2B IT or Qwen3.5 Flash?
Gemma 4 E2B IT is cheaper at $0.07 input / $0.09 output per million tokens (median across 2 API providers). Qwen3.5 Flash costs $0.10 input / $0.40 output per million tokens (official Alibaba API price); Gemma 4 31B IT costs $0.14 input / $0.40 output per million tokens (median across 30 API providers). At a typical mix of three input tokens to one output token, that is $0.075 per million tokens for Gemma 4 E2B IT versus $0.175 for Qwen3.5 Flash (2.3× as much) and $0.205 for Gemma 4 31B IT (2.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma 4 31B IT has an ECI of 142.8, Gemma 4 E2B IT has not been scored yet and Qwen3.5 Flash has an ECI of 144.0.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 4 31B IT, Gemma 4 E2B IT and Qwen3.5 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?
Qwen3.5 Flash has the largest context window at 1,000,000 tokens, against 262,144 for Gemma 4 31B IT and 131,072 for Gemma 4 E2B IT. Maximum output per response: Gemma 4 31B IT up to 32,768, Gemma 4 E2B IT up to 8,192, Qwen3.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemma 4 31B IT accepts text and images; Gemma 4 E2B IT accepts text, images and audio; Qwen3.5 Flash accepts text, images and video. Gemma 4 E2B IT handles the widest range of inputs.
Are any of these open source?
Gemma 4 31B IT and Gemma 4 E2B IT publishes its weights and can be self-hosted; Qwen3.5 Flash is proprietary.
Which is newer?
Gemma 4 31B IT is the newest, released Apr 2, 2026. Gemma 4 E2B IT came out Apr 2, 2026; Qwen3.5 Flash came out Feb 23, 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.