ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Voxtral Small 24B 2507 vs Granite-4.0-H-Micro vs Qwen Flash

Too close to call on our weighted score (Qwen Flash 68, Granite-4.0-H-Micro 65, Voxtral Small 24B 2507 55). The right pick depends on what you value most.

  1. Mistral AI

    Voxtral Small 24B 2507

    Released Jul 15, 2025

    55/100
    • ECI—
    • Price$0.10 / $0.30
    • Context33K
  2. IBM

    Granite-4.0-H-Micro

    Released Oct 2, 2025

    65/100
    • ECI—
    • Price$0.017 / $0.112
    • Context131K
  3. Alibaba (Qwen)

    Qwen Flash

    Released Jul 28, 2025

    68/100
    • ECI—
    • Price$0.05 / $0.40
    • Context1M
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Qwen Flash 68/100, Granite-4.0-H-Micro 65/100, Voxtral Small 24B 2507 55/100), so choose by what matters most for your work: Granite-4.0-H-Micro on price and Qwen 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 priceGranite-4.0-H-MicroGranite-4.0-H-Micro $0.041 · Qwen Flash $0.138 · Voxtral Small 24B 2507 $0.15 per 1M tokens (3:1 blend)
  • Longest contextQwen FlashQwen Flash 1,000,000 · Granite-4.0-H-Micro 131,072 · Voxtral Small 24B 2507 32,768 tokens
  • Widest inputsVoxtral Small 24B 2507Voxtral Small 24B 2507: Text, Audio · Granite-4.0-H-Micro: Text · Qwen Flash: Text
  • Self-hostingVoxtral Small 24B 2507 and Granite-4.0-H-MicroPublishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightVoxtral Small 24B 2507Granite-4.0-H-MicroQwen Flash
Price50%8910091
Inputs & features30%353535
Context window20%02460
Overall100%55/10065/10068/100

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.

Voxtral Small 24B 2507 vs Granite-4.0-H-Micro vs Qwen Flash specifications side by side
SpecificationVoxtral Small 24B 2507Mistral AIGranite-4.0-H-MicroIBMQwen FlashAlibaba (Qwen)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.10$0.017 (best)$0.05
Output$0.30$0.112 (best)$0.40
Cached input———
Blended (3:1)$0.15$0.041 (best)$0.138
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 1 providersOfficial Alibaba API
Limits
Context window32,768 tokens131,072 tokens1,000,000 tokens (best)
Max output32,768 tokens131,072 tokens (best)32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioYesNoNo
VideoNoNoNo
ReasoningNoNoYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenApache 2.0OpenProprietary
API model IDvoxtral-small-latest—qwen-flash
API providers7 (best)16
ReleasedJul 15, 2025Oct 2, 2025Jul 28, 2025
Knowledge cutoff——Apr 2024
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.

  • Voxtral Small 24B 2507$1.60
  • Granite-4.0-H-Micro$0.394
  • Qwen Flash$1.30
04 — Questions

Which should you choose?

Which is better: Voxtral Small 24B 2507, Granite-4.0-H-Micro or Qwen Flash?

It is close. Our weighted score puts them within 2 points (Qwen Flash 68/100, Granite-4.0-H-Micro 65/100, Voxtral Small 24B 2507 55/100), so choose by what matters most for your work: Granite-4.0-H-Micro on price and Qwen 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, Voxtral Small 24B 2507, Granite-4.0-H-Micro or Qwen Flash?

Granite-4.0-H-Micro is cheaper at $0.017 input / $0.112 output per million tokens (median across 1 API provider). Qwen Flash costs $0.05 input / $0.40 output per million tokens (official Alibaba API price); Voxtral Small 24B 2507 costs $0.10 input / $0.30 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.041 per million tokens for Granite-4.0-H-Micro versus $0.138 for Qwen Flash (3.4× as much) and $0.15 for Voxtral Small 24B 2507 (3.7× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Voxtral Small 24B 2507 has not been scored yet, Granite-4.0-H-Micro has not been scored yet and Qwen Flash has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Voxtral Small 24B 2507, Granite-4.0-H-Micro and Qwen 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?

Qwen Flash has the largest context window at 1,000,000 tokens, against 131,072 for Granite-4.0-H-Micro and 32,768 for Voxtral Small 24B 2507. Maximum output per response: Voxtral Small 24B 2507 up to 32,768, Granite-4.0-H-Micro up to 131,072, Qwen Flash up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Voxtral Small 24B 2507 accepts text and audio; Granite-4.0-H-Micro accepts text; Qwen Flash accepts text. Voxtral Small 24B 2507 handles the widest range of inputs.

Are any of these open source?

Voxtral Small 24B 2507 and Granite-4.0-H-Micro publishes its weights (Apache 2.0) and can be self-hosted; Qwen Flash is proprietary.

Which is newer?

Granite-4.0-H-Micro is the newest, released Oct 2, 2025. Qwen Flash came out Jul 28, 2025; Voxtral Small 24B 2507 came out Jul 15, 2025. Knowledge cutoff: Qwen Flash Apr 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.