ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Mistral Small 3.2 vs GLM-4.7-Flash

Mistral Small 3.2 comes out ahead, 51 to 47 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025Deprecated

    51/100
    • ECI—
    • Price$0.10 / $0.30
    • Context128K
    Full specs Remove Mistral Small 3.2

  2. 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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Mistral Small 3.2 is our pick

Mistral Small 3.2 is the better all-round choice, scoring 51/100 against GLM-4.7-Flash (47). It leads on capability and inputs & features. GLM-4.7-Flash wins on context window. 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 Mistral Small 3.2 and GLM-4.7-Flash has no Capabilities Index score yet.

  • CapabilityMistral Small 3.2Shared benchmarks: Mistral Small 3.2 39.7% · GLM-4.7-Flash 35.1%
  • Lowest priceMistral Small 3.2Mistral Small 3.2 $0.15 · GLM-4.7-Flash $0.152 per 1M tokens (3:1 blend)
  • Longest contextGLM-4.7-FlashGLM-4.7-Flash 200,000 · Mistral Small 3.2 128,000 tokens
  • Widest inputsMistral Small 3.2Mistral Small 3.2: Text, Images · GLM-4.7-Flash: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Small 3.2GLM-4.7-Flash
CapabilityShared benchmarks50%4035
Price25%8585
Inputs & features15%5035
Context window10%2432
Overall100%51/10047/100
02 — Side by side

Every spec in one table

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

Mistral Small 3.2 vs GLM-4.7-Flash specifications side by side
SpecificationMistral Small 3.2Mistral AIGLM-4.7-FlashZ.ai (Zhipu)
Capability
Capabilities Index (ECI)——
ECI rank——
GPQA DiamondGraduate-level science questions49.1% (best)45.1%
OTIS Mock AIME 2024–2025Competition mathematics30.3% (best)25.0%
Price per million tokens
Input$0.10$0.07 (best)
Output$0.30 (best)$0.40
Cached input——
Blended (3:1)$0.15 (best)$0.152
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 15 providers
Limits
Context window128,000 tokens200,000 tokens (best)
Max output16,384 tokens131,072 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDmistral-small-2506glm-4.7-flash
API providers724 (best)
ReleasedJun 20, 2025Jan 19, 2026
Knowledge cutoffMar 2025Apr 2025
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.

  • Mistral Small 3.2$1.60
  • GLM-4.7-Flash$1.50
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.2 or GLM-4.7-Flash?

Mistral Small 3.2 is the better all-round choice, scoring 51/100 against GLM-4.7-Flash (47). It leads on capability and inputs & features. GLM-4.7-Flash wins on context window. 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 Mistral Small 3.2 and GLM-4.7-Flash has no Capabilities Index score yet.

Which is cheaper, Mistral Small 3.2 or GLM-4.7-Flash?

Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). GLM-4.7-Flash costs $0.07 input / $0.40 output per million tokens (median across 15 API providers; free on Z.AI). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Small 3.2 versus $0.152 for GLM-4.7-Flash (1× 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): Mistral Small 3.2 39.7% and GLM-4.7-Flash 35.1%. On individual benchmarks: GPQA Diamond — Mistral Small 3.2 49.1%, GLM-4.7-Flash 45.1%; OTIS Mock AIME 2024–2025 — Mistral Small 3.2 30.3%, GLM-4.7-Flash 25.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Small 3.2 and GLM-4.7-Flash yet, so there is no like-for-like coding score. On overall capability, Mistral Small 3.2 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 3.2. Maximum output per response: Mistral Small 3.2 up to 16,384, GLM-4.7-Flash up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.2 accepts text and images; GLM-4.7-Flash accepts text. Mistral Small 3.2 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 3.2 came out Jun 20, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025, GLM-4.7-Flash Apr 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.

05 — Keep comparing

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