ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Mistral Small 3.2 vs GPT OSS 120B

Too close to call on our weighted score (GPT OSS 120B 61, Mistral Small 3.2 60). The right pick depends on what you value most.

  1. Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025

    60/100
    • ECI131.7
    • Price$0.10 / $0.30
    • Context128K
    Full specs Remove Mistral Small 3.2

  2. OpenAI

    GPT OSS 120B

    Released Aug 5, 2025

    61/100
    • ECI140.0
    • Price$0.15 / $0.60
    • Context131K
    Full specs Remove GPT OSS 120B

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GPT OSS 120B 61/100, Mistral Small 3.2 60/100), so choose by what matters most for your work: GPT OSS 120B for raw capability and Mistral Small 3.2 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT OSS 120BCapabilities Index (ECI): GPT OSS 120B 140.0 · Mistral Small 3.2 131.7
  • Lowest priceMistral Small 3.2Mistral Small 3.2 $0.15 · GPT OSS 120B $0.263 per 1M tokens (3:1 blend)
  • Longest contextGPT OSS 120BGPT OSS 120B 131,072 · Mistral Small 3.2 128,000 tokens
  • Widest inputsMistral Small 3.2Mistral Small 3.2: Text, Images · GPT OSS 120B: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Small 3.2GPT OSS 120B
CapabilityCapabilities Index (ECI)50%5565
Price25%8977
Inputs & features15%5045
Context window10%2424
Overall100%60/10061/100
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 GPT OSS 120B specifications side by side
SpecificationMistral Small 3.2Mistral AIGPT OSS 120BOpenAI
Capability
Capabilities Index (ECI)131.7140.0 (best)
ECI rank#123 of 148#99 of 148 (best)
GPQA DiamondGraduate-level science questions49.1%75.8% (best)
OTIS Mock AIME 2024–2025Competition mathematics30.3%88.9% (best)
Price per million tokens
Input$0.10 (best)$0.15
Output$0.30 (best)$0.60
Cached input——
Blended (3:1)$0.15 (best)$0.263
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 36 providers
Limits
Context window128,000 tokens131,072 tokens (best)
Max output16,384 tokens32,768 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenOpen
API model IDmistral-small-2506—
API providers639 (best)
ReleasedJun 20, 2025Aug 5, 2025
Knowledge cutoffMar 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
  • GPT OSS 120B$2.70
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.2 or GPT OSS 120B?

It is close. Our weighted score puts them within 2 points (GPT OSS 120B 61/100, Mistral Small 3.2 60/100), so choose by what matters most for your work: GPT OSS 120B for raw capability and Mistral Small 3.2 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Small 3.2 or GPT OSS 120B?

Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). GPT OSS 120B costs $0.15 input / $0.60 output per million tokens (median across 36 API providers). 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 $0.263 for GPT OSS 120B (1.8× as much).

Which scores higher on benchmarks?

GPT OSS 120B scores higher on the Capabilities Index (ECI): GPT OSS 120B 140.0 (#99 of 148) and Mistral Small 3.2 131.7 (#123 of 148). Their confidence ranges do not overlap (135.3–142.3 vs 126.6–133.9), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT OSS 120B 75.8%, Mistral Small 3.2 49.1%; OTIS Mock AIME 2024–2025 — GPT OSS 120B 88.9%, Mistral Small 3.2 30.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Small 3.2 and GPT OSS 120B yet, so there is no like-for-like coding score. On overall capability, GPT OSS 120B 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?

GPT OSS 120B has the largest context window at 131,072 tokens, against 128,000 for Mistral Small 3.2. Maximum output per response: Mistral Small 3.2 up to 16,384, GPT OSS 120B up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.2 accepts text and images; GPT OSS 120B 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?

GPT OSS 120B is the newest, released Aug 5, 2025. Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: 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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