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Comparison · 3 models · Updated Nov 2, 2026

Qwen3.5 2B vs Granite-4.0-H-Micro vs Gemma 4 E4B IT

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.

  1. Alibaba (Qwen)

    Qwen3.5 2B

    Released Mar 2, 2026

    78/100
    • ECI—
    • Price$0.02 / $0.10
    • Context262K
  2. IBM

    Granite-4.0-H-Micro

    Released Oct 2, 2025

    62/100
    • ECI—
    • Price$0.018 / $0.115
    • Context131K
  3. Google

    Gemma 4 E4B IT

    Released Apr 2, 2026

    76/100
    • ECI—
    • Price$0.02 / $0.10
    • Context131K
01 — Verdict

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: Qwen3.5 2B 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 priceQwen3.5 2B and Gemma 4 E4B ITQwen3.5 2B $0.04 · Gemma 4 E4B IT $0.04 · Granite-4.0-H-Micro $0.042 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 2BQwen3.5 2B 262,144 · Granite-4.0-H-Micro 131,072 · Gemma 4 E4B IT 131,072 tokens
  • Widest inputsQwen3.5 2B and Gemma 4 E4B ITQwen3.5 2B: Text, Images, Video · Granite-4.0-H-Micro: Text · Gemma 4 E4B IT: Text, Images, Audio
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3.5 2BGranite-4.0-H-MicroGemma 4 E4B IT
Price50%100100100
Inputs & features30%702570
Context window20%372525
Overall100%78/10062/10076/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen3.5 2B vs Granite-4.0-H-Micro vs Gemma 4 E4B IT specifications side by side
SpecificationQwen3.5 2BAlibaba (Qwen)Granite-4.0-H-MicroIBMGemma 4 E4B ITGoogle
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 rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 2 providersMedian of 1 providers
Limits
Context window262,144 tokens (best)131,072 tokens131,072 tokens
Max output81,920 tokens131,072 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoNo
AudioNoNoYes
VideoYesNoNo
ReasoningYesNoYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenApache-2.0OpenOpen
API model ID———
API providers222
ReleasedMar 2, 2026Oct 2, 2025Apr 2, 2026
Knowledge cutoff———
03 — Cost

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 2B$0.40
  • Granite-4.0-H-Micro$0.405
  • Gemma 4 E4B IT$0.40
04 — Questions

Which should you choose?

Which is better: Qwen3.5 2B, Granite-4.0-H-Micro or Gemma 4 E4B IT?

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: Qwen3.5 2B 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, Qwen3.5 2B, Granite-4.0-H-Micro or Gemma 4 E4B IT?

Qwen3.5 2B is cheaper at $0.02 input / $0.10 output per million tokens (median across 1 API provider). Gemma 4 E4B IT 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 Qwen3.5 2B versus $0.04 for Gemma 4 E4B IT (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. Qwen3.5 2B has not been scored yet, Granite-4.0-H-Micro has not been scored yet and Gemma 4 E4B IT has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 2B, Granite-4.0-H-Micro and Gemma 4 E4B IT 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 Granite-4.0-H-Micro and 131,072 for Gemma 4 E4B IT. Maximum output per response: Qwen3.5 2B up to 81,920, Granite-4.0-H-Micro up to 131,072, Gemma 4 E4B IT up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Qwen3.5 2B accepts text, images and video; Granite-4.0-H-Micro accepts text; Gemma 4 E4B IT accepts text, images and audio. Qwen3.5 2B 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.