ZMIME
Comparison · 2 models · Updated Nov 2, 2026

GLM-4.7-Flash vs Mistral Small 3.1 24B

GLM-4.7-Flash comes out ahead, 47 to 40 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Z.ai (Zhipu)

    GLM-4.7-Flash

    Released Jan 19, 2026

    47/100
    • ECI—
    • Price$0.07 / $0.40
    • Context200K
    Full specs Remove GLM-4.7-Flash

  2. Mistral AI

    Mistral Small 3.1 24B

    Released Mar 17, 2025

    40/100
    • ECI127.5
    • Price$0.351 / $0.555
    • Context128K
    Full specs Remove Mistral Small 3.1 24B

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GLM-4.7-Flash is our pick

GLM-4.7-Flash is the better all-round choice, scoring 47/100 against Mistral Small 3.1 24B (40). It leads on capability, price and context window. Mistral Small 3.1 24B wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GLM-4.7-Flash has no Capabilities Index score yet.

  • CapabilityGLM-4.7-FlashShared benchmarks: GLM-4.7-Flash 35.1% · Mistral Small 3.1 24B 26.7%
  • Lowest priceGLM-4.7-FlashGLM-4.7-Flash $0.152 · Mistral Small 3.1 24B $0.402 per 1M tokens (3:1 blend)
  • Longest contextGLM-4.7-FlashGLM-4.7-Flash 200,000 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsMistral Small 3.1 24BGLM-4.7-Flash: Text · Mistral Small 3.1 24B: Text, Images
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGLM-4.7-FlashMistral Small 3.1 24B
CapabilityShared benchmarks50%3527
Price25%8566
Inputs & features15%3550
Context window10%3224
Overall100%47/10040/100
02 — Side by side

Every spec in one table

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

GLM-4.7-Flash vs Mistral Small 3.1 24B specifications side by side
SpecificationGLM-4.7-FlashZ.ai (Zhipu)Mistral Small 3.1 24BMistral AI
Capability
Capabilities Index (ECI)—127.5
ECI rank—#145 of 165
GPQA DiamondGraduate-level science questions45.1%47.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics25.0% (best)5.8%
Price per million tokens
Input$0.07 (best)$0.351
Output$0.40 (best)$0.555
Cached input——
Blended (3:1)$0.152 (best)$0.402
Long-context rateSame rateSame rate
Price sourceMedian of 15 providersMedian of 9 providers
Limits
Context window200,000 tokens (best)128,000 tokens
Max output131,072 tokens (best)16,384 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDglm-4.7-flash—
API providers24 (best)9
ReleasedJan 19, 2026Mar 17, 2025
Knowledge cutoffApr 2025Jun 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-4.7-Flash$1.50
  • Mistral Small 3.1 24B$4.62
04 — Questions

Which should you choose?

Which is better: GLM-4.7-Flash or Mistral Small 3.1 24B?

GLM-4.7-Flash is the better all-round choice, scoring 47/100 against Mistral Small 3.1 24B (40). It leads on capability, price and context window. Mistral Small 3.1 24B wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GLM-4.7-Flash has no Capabilities Index score yet.

Which is cheaper, GLM-4.7-Flash or Mistral Small 3.1 24B?

GLM-4.7-Flash is cheaper at $0.07 input / $0.40 output per million tokens (median across 15 API providers; free on Z.AI). Mistral Small 3.1 24B costs $0.351 input / $0.555 output per million tokens (median across 9 API providers). At a typical mix of three input tokens to one output token, that is $0.152 per million tokens for GLM-4.7-Flash versus $0.402 for Mistral Small 3.1 24B (2.6× as much).

Which scores higher on benchmarks?

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): GLM-4.7-Flash 35.1% and Mistral Small 3.1 24B 26.7%. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, GLM-4.7-Flash 45.1%; OTIS Mock AIME 2024–2025 — GLM-4.7-Flash 25.0%, Mistral Small 3.1 24B 5.8%.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.7-Flash and Mistral Small 3.1 24B yet, so there is no like-for-like coding score. On overall capability, GLM-4.7-Flash leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

GLM-4.7-Flash has the largest context window at 200,000 tokens, against 128,000 for Mistral Small 3.1 24B. Maximum output per response: GLM-4.7-Flash up to 131,072, Mistral Small 3.1 24B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7-Flash accepts text; Mistral Small 3.1 24B accepts text and images. Mistral Small 3.1 24B handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

GLM-4.7-Flash is the newest, released Jan 19, 2026. Mistral Small 3.1 24B came out Mar 17, 2025. Knowledge cutoff: GLM-4.7-Flash Apr 2025, Mistral Small 3.1 24B Jun 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 Nov 2, 2026.

05 — Keep comparing

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