ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GLM-4.7-Flash vs Mistral Small 3.2

Mistral Small 3.2 comes out ahead, 52 to 48 on our weighted score.

  1. Z.ai (Zhipu)

    GLM-4.7-Flash

    Released Jan 19, 2026

    48/100
    • ECI—
    • Price$0.06 / $0.40
    • Context200K
    Full specs Remove GLM-4.7-Flash
  2. Our pick

    Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025

    52/100
    • ECI131.7
    • Price$0.10 / $0.30
    • Context128K
    Full specs Remove Mistral Small 3.2

  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 52/100 against GLM-4.7-Flash (48). 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 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 priceGLM-4.7-FlashGLM-4.7-Flash $0.145 · Mistral Small 3.2 $0.15 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 3.2GLM-4.7-Flash: Text · Mistral Small 3.2: 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 3.2
CapabilityShared benchmarks50%3540
Price25%9089
Inputs & features15%3550
Context window10%3224
Overall100%48/10052/100
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 3.2 specifications side by side
SpecificationGLM-4.7-FlashZ.ai (Zhipu)Mistral Small 3.2Mistral AI
Capability
Capabilities Index (ECI)—131.7
ECI rank—#123 of 148
GPQA DiamondGraduate-level science questions45.1%49.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics25.0%30.3% (best)
Price per million tokens
Input$0.06 (best)$0.10
Output$0.40$0.30 (best)
Cached input——
Blended (3:1)$0.145 (best)$0.15
Long-context rateSame rateSame rate
Price sourceMedian of 13 providersOfficial Mistral API
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-flashmistral-small-2506
API providers19 (best)6
ReleasedJan 19, 2026Jun 20, 2025
Knowledge cutoffApr 2025Mar 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.

  • GLM-4.7-Flash$1.41
  • Mistral Small 3.2$1.60
04 — Questions

Which should you choose?

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

Mistral Small 3.2 is the better all-round choice, scoring 52/100 against GLM-4.7-Flash (48). 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 GLM-4.7-Flash has no Capabilities Index score yet.

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

GLM-4.7-Flash is cheaper at $0.06 input / $0.40 output per million tokens (median across 13 API providers; free on Z.AI). Mistral Small 3.2 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 $0.145 per million tokens for GLM-4.7-Flash versus $0.15 for Mistral Small 3.2 (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 GLM-4.7-Flash and Mistral Small 3.2 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: GLM-4.7-Flash up to 131,072, Mistral Small 3.2 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7-Flash accepts text; Mistral Small 3.2 accepts text and images. 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: GLM-4.7-Flash Apr 2025, Mistral Small 3.2 Mar 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 Oct 4, 2026.

05 — Keep comparing

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