ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GLM-4.7-FlashX vs Mistral Small 3.2

Mistral Small 3.2 comes out ahead, 64 to 61 on our weighted score, and it is the cheaper option too.

  1. Z.ai (Zhipu)

    GLM-4.7-FlashX

    Released Jan 19, 2026

    61/100
    • ECI—
    • Price$0.07 / $0.40
    • Context200K
    Full specs Remove GLM-4.7-FlashX
  2. Our pick

    Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025

    64/100
    • 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 64/100 against GLM-4.7-FlashX (61). It leads on inputs & features. GLM-4.7-FlashX wins on context window. 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 priceMistral Small 3.2Mistral Small 3.2 $0.15 · GLM-4.7-FlashX $0.152 per 1M tokens (3:1 blend)
  • Longest contextGLM-4.7-FlashXGLM-4.7-FlashX 200,000 · Mistral Small 3.2 128,000 tokens
  • Widest inputsMistral Small 3.2GLM-4.7-FlashX: 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-FlashXMistral Small 3.2
Price50%8989
Inputs & features30%3550
Context window20%3224
Overall100%61/10064/100

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-4.7-FlashX vs Mistral Small 3.2 specifications side by side
SpecificationGLM-4.7-FlashXZ.ai (Zhipu)Mistral Small 3.2Mistral AI
Capability
Capabilities Index (ECI)—131.7
ECI rank—#123 of 148
GPQA DiamondGraduate-level science questions—49.1%
OTIS Mock AIME 2024–2025Competition mathematics—30.3%
Price per million tokens
Input$0.07 (best)$0.10
Output$0.40$0.30 (best)
Cached input$0.01—
Blended (3:1)$0.152$0.15 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial 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-flashxmistral-small-2506
API providers8 (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-FlashX$1.50
  • Mistral Small 3.2$1.60
04 — Questions

Which should you choose?

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

Mistral Small 3.2 is the better all-round choice, scoring 64/100 against GLM-4.7-FlashX (61). It leads on inputs & features. GLM-4.7-FlashX wins on context window. 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-4.7-FlashX or Mistral Small 3.2?

Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). GLM-4.7-FlashX costs $0.07 input / $0.40 output per million tokens (official Z.AI API price). 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-FlashX (1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. GLM-4.7-FlashX has not been scored yet and Mistral Small 3.2 has an ECI of 131.7.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.7-FlashX and Mistral Small 3.2 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

GLM-4.7-FlashX has the largest context window at 200,000 tokens, against 128,000 for Mistral Small 3.2. Maximum output per response: GLM-4.7-FlashX up to 131,072, Mistral Small 3.2 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7-FlashX 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-FlashX is the newest, released Jan 19, 2026. Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: GLM-4.7-FlashX 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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