ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GPT-5 Nano vs Mistral Small 3.2 vs Qwen3.5 9B

Too close to call on our weighted score (Qwen3.5 9B 72, GPT-5 Nano 70, Mistral Small 3.2 60). The right pick depends on what you value most.

  1. OpenAI

    GPT-5 Nano

    Released Aug 7, 2025

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

  2. 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

  3. Alibaba (Qwen)

    Qwen3.5 9B

    Released Feb 23, 2026

    72/100
    • ECI139.5
    • Price$0.10 / $0.15
    • Context262K
    Full specs Remove Qwen3.5 9B
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, Mistral Small 3.2 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and GPT-5 Nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · GPT-5 Nano 139.4 · Mistral Small 3.2 131.7
  • Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · GPT-5 Nano $0.138 · Mistral Small 3.2 $0.15 per 1M tokens (3:1 blend)
  • Longest contextGPT-5 NanoGPT-5 Nano 400,000 · Qwen3.5 9B 262,144 · Mistral Small 3.2 128,000 tokens
  • Widest inputsQwen3.5 9BGPT-5 Nano: Text, Images · Mistral Small 3.2: Text, Images · Qwen3.5 9B: Text, Images, Video
  • Self-hostingMistral Small 3.2 and Qwen3.5 9BPublishes downloadable weights
How the score is built
MeasureWeightGPT-5 NanoMistral Small 3.2Qwen3.5 9B
CapabilityCapabilities Index (ECI)50%655565
Price25%918995
Inputs & features15%705080
Context window10%442437
Overall100%70/10060/10072/100
02 — Side by side

Every spec in one table

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

GPT-5 Nano vs Mistral Small 3.2 vs Qwen3.5 9B specifications side by side
SpecificationGPT-5 NanoOpenAIMistral Small 3.2Mistral AIQwen3.5 9BAlibaba (Qwen)
Capability
Capabilities Index (ECI)139.4131.7139.5 (best)
ECI rank#102 of 148#123 of 148#101 of 148 (best)
GPQA DiamondGraduate-level science questions69.4%49.1%79.0% (best)
FrontierMath Tiers 1–3Research-level mathematics20.0%——
OTIS Mock AIME 2024–2025Competition mathematics81.1% (best)30.3%61.7%
SimpleQA VerifiedShort factual questions11.7%——
Price per million tokens
Input$0.05 (best)$0.10$0.10
Output$0.40$0.30$0.15 (best)
Cached input$0.005——
Blended (3:1)$0.138$0.15$0.113 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial OpenAI APIOfficial Mistral APIMedian of 14 providers
Limits
Context window400,000 tokens (best)128,000 tokens262,144 tokens
Max output128,000 tokens (best)16,384 tokens65,536 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningYesminimal · low · medium · highNoYes
Tool callingYesYesYes
Structured outputYesNoYes
Availability
WeightsProprietaryOpenOpen
API model IDgpt-5-nanomistral-small-2506—
API providers21 (best)615
ReleasedAug 7, 2025Jun 20, 2025Feb 23, 2026
Knowledge cutoffMay 30, 2024Mar 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.

  • GPT-5 Nano$1.30
  • Mistral Small 3.2$1.60
  • Qwen3.5 9B$1.30
04 — Questions

Which should you choose?

Which is better: GPT-5 Nano, Mistral Small 3.2 or Qwen3.5 9B?

It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, Mistral Small 3.2 60/100), so choose by what matters most for your work: Qwen3.5 9B for raw capability and GPT-5 Nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-5 Nano, Mistral Small 3.2 or Qwen3.5 9B?

Qwen3.5 9B is cheaper at $0.10 input / $0.15 output per million tokens (median across 14 API providers). GPT-5 Nano costs $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 $0.113 per million tokens for Qwen3.5 9B versus $0.138 for GPT-5 Nano (1.2× as much) and $0.15 for Mistral Small 3.2 (1.3× as much).

Which scores higher on benchmarks?

Qwen3.5 9B scores higher on the Capabilities Index (ECI): Qwen3.5 9B 139.5 (#101 of 148), GPT-5 Nano 139.4 (#102 of 148) and Mistral Small 3.2 131.7 (#123 of 148). The confidence ranges of the top two overlap (136.5–141.3 vs 134.9–141.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, GPT-5 Nano 69.4%, Mistral Small 3.2 49.1%; OTIS Mock AIME 2024–2025 — GPT-5 Nano 81.1%, Qwen3.5 9B 61.7%, Mistral Small 3.2 30.3%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-5 Nano, Mistral Small 3.2 and Qwen3.5 9B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 9B leads, which tends to carry over to coding, but test on your own codebase. All three 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 262,144 for Qwen3.5 9B and 128,000 for Mistral Small 3.2. Maximum output per response: GPT-5 Nano up to 128,000, Mistral Small 3.2 up to 16,384, Qwen3.5 9B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

GPT-5 Nano accepts text and images; Mistral Small 3.2 accepts text and images; Qwen3.5 9B accepts text, images and video. Qwen3.5 9B handles the widest range of inputs.

Are any of these open source?

Mistral Small 3.2 and Qwen3.5 9B publishes its weights and can be self-hosted; GPT-5 Nano is proprietary.

Which is newer?

Qwen3.5 9B is the newest, released Feb 23, 2026. GPT-5 Nano came out Aug 7, 2025; Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: GPT-5 Nano May 30, 2024, 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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