ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GLM-4.5-Flash vs Qwen Flash vs Voxtral Small 24B 2507

Too close to call on our weighted score (Qwen Flash 68, GLM-4.5-Flash 65, Voxtral Small 24B 2507 55). The right pick depends on what you value most.

  1. Z.ai (Zhipu)

    GLM-4.5-Flash

    Released Jul 28, 2025

    65/100
    • ECI—
    • PriceFree / Free
    • Context131K
  2. Alibaba (Qwen)

    Qwen Flash

    Released Jul 28, 2025

    68/100
    • ECI—
    • Price$0.05 / $0.40
    • Context1M
  3. Mistral AI

    Voxtral Small 24B 2507

    Released Jul 15, 2025

    55/100
    • ECI—
    • Price$0.10 / $0.30
    • Context33K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Qwen Flash 68/100, GLM-4.5-Flash 65/100, Voxtral Small 24B 2507 55/100), so choose by what matters most for your work: GLM-4.5-Flash 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 priceGLM-4.5-FlashGLM-4.5-Flash Free · Qwen Flash $0.138 · Voxtral Small 24B 2507 $0.15 per 1M tokens (3:1 blend)
  • Longest contextQwen FlashQwen Flash 1,000,000 · GLM-4.5-Flash 131,072 · Voxtral Small 24B 2507 32,768 tokens
  • Widest inputsVoxtral Small 24B 2507GLM-4.5-Flash: Text · Qwen Flash: Text · Voxtral Small 24B 2507: Text, Audio
  • Self-hostingVoxtral Small 24B 2507Publishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightGLM-4.5-FlashQwen FlashVoxtral Small 24B 2507
Price50%1009189
Inputs & features30%353535
Context window20%24600
Overall100%65/10068/10055/100

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.

GLM-4.5-Flash vs Qwen Flash vs Voxtral Small 24B 2507 specifications side by side
SpecificationGLM-4.5-FlashZ.ai (Zhipu)Qwen FlashAlibaba (Qwen)Voxtral Small 24B 2507Mistral AI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
InputFree (best)$0.05$0.10
OutputFree (best)$0.40$0.30
Cached input———
Blended (3:1)Free (best)$0.138$0.15
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial Alibaba APIOfficial Mistral API
Limits
Context window131,072 tokens1,000,000 tokens (best)32,768 tokens
Max output98,304 tokens (best)32,768 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoYes
VideoNoNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryProprietaryOpenApache 2.0
API model IDglm-4.5-flashqwen-flashvoxtral-small-latest
API providers467 (best)
ReleasedJul 28, 2025Jul 28, 2025Jul 15, 2025
Knowledge cutoffApr 2025Apr 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.

  • GLM-4.5-FlashFree
  • Qwen Flash$1.30
  • Voxtral Small 24B 2507$1.60
04 — Questions

Which should you choose?

Which is better: GLM-4.5-Flash, Qwen Flash or Voxtral Small 24B 2507?

It is close. Our weighted score puts them within 2 points (Qwen Flash 68/100, GLM-4.5-Flash 65/100, Voxtral Small 24B 2507 55/100), so choose by what matters most for your work: GLM-4.5-Flash 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, GLM-4.5-Flash, Qwen Flash or Voxtral Small 24B 2507?

GLM-4.5-Flash is cheaper at Free input / Free output per million tokens (official Z.AI API price). 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). GLM-4.5-Flash is listed as free.

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. GLM-4.5-Flash has not been scored yet, Qwen Flash has not been scored yet and Voxtral Small 24B 2507 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.5-Flash, Qwen Flash and Voxtral Small 24B 2507 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 GLM-4.5-Flash and 32,768 for Voxtral Small 24B 2507. Maximum output per response: GLM-4.5-Flash up to 98,304, Qwen Flash up to 32,768, Voxtral Small 24B 2507 up to 32,768 tokens.

Which can read images, PDFs, audio or video?

GLM-4.5-Flash accepts text; Qwen Flash accepts text; Voxtral Small 24B 2507 accepts text and audio. Voxtral Small 24B 2507 handles the widest range of inputs.

Are any of these open source?

Voxtral Small 24B 2507 publishes its weights (Apache 2.0) and can be self-hosted; GLM-4.5-Flash and Qwen Flash is proprietary.

Which is newer?

GLM-4.5-Flash is the newest, released Jul 28, 2025. Qwen Flash came out Jul 28, 2025; Voxtral Small 24B 2507 came out Jul 15, 2025. Knowledge cutoff: GLM-4.5-Flash Apr 2025, 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.