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Comparison · 2 models · Updated Oct 4, 2026

Mistral Small 3.2 vs GPT-5 Nano

GPT-5 Nano comes out ahead, 70 to 60 on our weighted score, and it is the cheaper option too.

  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. Our pick

    OpenAI

    GPT-5 Nano

    Released Aug 7, 2025

    70/100
    • ECI139.4
    • Price$0.05 / $0.40
    • Context400K
    Full specs Remove GPT-5 Nano

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GPT-5 Nano is our pick

GPT-5 Nano is the better all-round choice, scoring 70/100 against Mistral Small 3.2 (60). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5 NanoCapabilities Index (ECI): GPT-5 Nano 139.4 · Mistral Small 3.2 131.7
  • Lowest priceGPT-5 NanoGPT-5 Nano $0.138 · Mistral Small 3.2 $0.15 per 1M tokens (3:1 blend)
  • Longest contextGPT-5 NanoGPT-5 Nano 400,000 · Mistral Small 3.2 128,000 tokens
  • Widest inputsSame inputsMistral Small 3.2: Text, Images · GPT-5 Nano: Text, Images
  • Self-hostingMistral Small 3.2Publishes downloadable weights
How the score is built
MeasureWeightMistral Small 3.2GPT-5 Nano
CapabilityCapabilities Index (ECI)50%5565
Price25%8991
Inputs & features15%5070
Context window10%2444
Overall100%60/10070/100
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-5 Nano specifications side by side
SpecificationMistral Small 3.2Mistral AIGPT-5 NanoOpenAI
Capability
Capabilities Index (ECI)131.7139.4 (best)
ECI rank#123 of 148#102 of 148 (best)
GPQA DiamondGraduate-level science questions49.1%69.4% (best)
FrontierMath Tiers 1–3Research-level mathematics—20.0%
OTIS Mock AIME 2024–2025Competition mathematics30.3%81.1% (best)
SimpleQA VerifiedShort factual questions—11.7%
Price per million tokens
Input$0.10$0.05 (best)
Output$0.30 (best)$0.40
Cached input—$0.005
Blended (3:1)$0.15$0.138 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial OpenAI API
Limits
Context window128,000 tokens400,000 tokens (best)
Max output16,384 tokens128,000 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYesminimal · low · medium · high
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenProprietary
API model IDmistral-small-2506gpt-5-nano
API providers621 (best)
ReleasedJun 20, 2025Aug 7, 2025
Knowledge cutoffMar 2025May 30, 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.

  • Mistral Small 3.2$1.60
  • GPT-5 Nano$1.30
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.2 or GPT-5 Nano?

GPT-5 Nano is the better all-round choice, scoring 70/100 against Mistral Small 3.2 (60). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Small 3.2 or GPT-5 Nano?

GPT-5 Nano is cheaper at $0.05 input / $0.40 output per million tokens (official OpenAI API price). 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 $0.138 per million tokens for GPT-5 Nano versus $0.15 for Mistral Small 3.2 (1.1× as much).

Which scores higher on benchmarks?

GPT-5 Nano scores higher on the Capabilities Index (ECI): GPT-5 Nano 139.4 (#102 of 148) and Mistral Small 3.2 131.7 (#123 of 148). Their confidence ranges do not overlap (134.9–141.7 vs 126.6–133.9), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-5 Nano 69.4%, Mistral Small 3.2 49.1%; OTIS Mock AIME 2024–2025 — GPT-5 Nano 81.1%, 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-5 Nano yet, so there is no like-for-like coding score. On overall capability, GPT-5 Nano 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-5 Nano has the largest context window at 400,000 tokens, against 128,000 for Mistral Small 3.2. Maximum output per response: Mistral Small 3.2 up to 16,384, GPT-5 Nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.2 accepts text and images; GPT-5 Nano accepts text and images. They handle the same number of input types.

Are any of these open source?

Mistral Small 3.2 publishes its weights and can be self-hosted; GPT-5 Nano is proprietary.

Which is newer?

GPT-5 Nano is the newest, released Aug 7, 2025. Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025, GPT-5 Nano May 30, 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 Oct 4, 2026.

05 — Keep comparing

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