Gemma 4 E4B IT vs Granite-4.0-H-Micro vs Qwen3.5 2B
Too close to call on our weighted score (Qwen3.5 2B 78, Gemma 4 E4B IT 76, Granite-4.0-H-Micro 62). The right pick depends on what you value most.
Google
Gemma 4 E4B IT
76/100- ECI—
- Price$0.02 / $0.10
- Context131K
IBM
Granite-4.0-H-Micro
62/100- ECI—
- Price$0.018 / $0.115
- Context131K
Alibaba (Qwen)
Qwen3.5 2B
78/100- ECI—
- Price$0.02 / $0.10
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Qwen3.5 2B 78/100, Gemma 4 E4B IT 76/100, Granite-4.0-H-Micro 62/100), so choose by what matters most for your work: Gemma 4 E4B IT on price and Qwen3.5 2B 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 E4B IT and Qwen3.5 2BGemma 4 E4B IT $0.04 · Qwen3.5 2B $0.04 · Granite-4.0-H-Micro $0.042 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 2BQwen3.5 2B 262,144 · Gemma 4 E4B IT 131,072 · Granite-4.0-H-Micro 131,072 tokens
- Widest inputsGemma 4 E4B IT and Qwen3.5 2BGemma 4 E4B IT: Text, Images, Audio · Granite-4.0-H-Micro: Text · Qwen3.5 2B: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Gemma 4 E4B IT | Granite-4.0-H-Micro | Qwen3.5 2B |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 70 | 25 | 70 |
| Context window | 20% | 25 | 25 | 37 |
| Overall | 100% | 76/100 | 62/100 | 78/100 |
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) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.02 | $0.018 (best) | $0.02 |
| Output | $0.10 (best) | $0.115 | $0.10 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.04 (best) | $0.042 | $0.04 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 2 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 8,192 tokens | 131,072 tokens (best) | 81,920 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | OpenApache-2.0 |
| API model ID | — | — | — |
| API providers | 2 | 2 | 2 |
| Released | Apr 2, 2026 | Oct 2, 2025 | Mar 2, 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 E4B IT$0.40
Granite-4.0-H-Micro$0.405
Qwen3.5 2B$0.40
Which should you choose?
Which is better: Gemma 4 E4B IT, Granite-4.0-H-Micro or Qwen3.5 2B?
It is close. Our weighted score puts them within 2 points (Qwen3.5 2B 78/100, Gemma 4 E4B IT 76/100, Granite-4.0-H-Micro 62/100), so choose by what matters most for your work: Gemma 4 E4B IT on price and Qwen3.5 2B 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 E4B IT, Granite-4.0-H-Micro or Qwen3.5 2B?
Gemma 4 E4B IT is cheaper at $0.02 input / $0.10 output per million tokens (median across 1 API provider). Qwen3.5 2B costs $0.02 input / $0.10 output per million tokens (median across 1 API provider); Granite-4.0-H-Micro costs $0.018 input / $0.115 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.04 per million tokens for Gemma 4 E4B IT versus $0.04 for Qwen3.5 2B (1× as much) and $0.042 for Granite-4.0-H-Micro (1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma 4 E4B IT has not been scored yet, Granite-4.0-H-Micro has not been scored yet and Qwen3.5 2B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 4 E4B IT, Granite-4.0-H-Micro and Qwen3.5 2B 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 2B has the largest context window at 262,144 tokens, against 131,072 for Gemma 4 E4B IT and 131,072 for Granite-4.0-H-Micro. Maximum output per response: Gemma 4 E4B IT up to 8,192, Granite-4.0-H-Micro up to 131,072, Qwen3.5 2B up to 81,920 tokens.
Which can read images, PDFs, audio or video?
Gemma 4 E4B IT accepts text, images and audio; Granite-4.0-H-Micro accepts text; Qwen3.5 2B accepts text, images and video. Gemma 4 E4B IT handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Gemma 4 E4B IT is the newest, released Apr 2, 2026. Qwen3.5 2B came out Mar 2, 2026; Granite-4.0-H-Micro came out Oct 2, 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.