ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Gemma 3 27B IT vs Mistral Small 3.2 vs Qwen3.5 9B

Qwen3.5 9B comes out ahead, 72 to 60 and 60 on our weighted score.

  1. Google

    Gemma 3 27B IT

    Released Mar 12, 2025

    60/100
    • ECI130.0
    • Price$0.08 / $0.20
    • Context131K
    Full specs Remove Gemma 3 27B IT

  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. Our pick

    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

Qwen3.5 9B is our pick

Qwen3.5 9B is the better all-round choice, scoring 72/100 against Gemma 3 27B IT (60) and Mistral Small 3.2 (60). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · Mistral Small 3.2 131.7 · Gemma 3 27B IT 130.0
  • Lowest priceGemma 3 27B ITGemma 3 27B IT $0.11 · Qwen3.5 9B $0.113 · Mistral Small 3.2 $0.15 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 9BQwen3.5 9B 262,144 · Gemma 3 27B IT 131,072 · Mistral Small 3.2 128,000 tokens
  • Widest inputsQwen3.5 9BGemma 3 27B IT: Text, Images · Mistral Small 3.2: Text, Images · Qwen3.5 9B: Text, Images, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGemma 3 27B ITMistral Small 3.2Qwen3.5 9B
CapabilityCapabilities Index (ECI)50%535565
Price25%958995
Inputs & features15%505080
Context window10%242437
Overall100%60/10060/10072/100
02 — Side by side

Every spec in one table

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

Gemma 3 27B IT vs Mistral Small 3.2 vs Qwen3.5 9B specifications side by side
SpecificationGemma 3 27B ITGoogleMistral Small 3.2Mistral AIQwen3.5 9BAlibaba (Qwen)
Capability
Capabilities Index (ECI)130.0131.7139.5 (best)
ECI rank#125 of 148#123 of 148#101 of 148 (best)
GPQA DiamondGraduate-level science questions47.7%49.1%79.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics22.5%30.3%61.7% (best)
Price per million tokens
Input$0.08 (best)$0.10$0.10
Output$0.20$0.30$0.15 (best)
Cached input———
Blended (3:1)$0.11 (best)$0.15$0.113
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 9 providersOfficial Mistral APIMedian of 14 providers
Limits
Context window131,072 tokens128,000 tokens262,144 tokens (best)
Max output131,072 tokens (best)16,384 tokens65,536 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningNoNoYes
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenOpen
API model ID—mistral-small-2506—
API providers10615 (best)
ReleasedMar 12, 2025Jun 20, 2025Feb 23, 2026
Knowledge cutoffAug 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.

  • Gemma 3 27B IT$1.20
  • Mistral Small 3.2$1.60
  • Qwen3.5 9B$1.30
04 — Questions

Which should you choose?

Which is better: Gemma 3 27B IT, Mistral Small 3.2 or Qwen3.5 9B?

Qwen3.5 9B is the better all-round choice, scoring 72/100 against Gemma 3 27B IT (60) and Mistral Small 3.2 (60). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemma 3 27B IT, Mistral Small 3.2 or Qwen3.5 9B?

Gemma 3 27B IT is cheaper at $0.08 input / $0.20 output per million tokens (median across 9 API providers). Qwen3.5 9B costs $0.10 input / $0.15 output per million tokens (median across 14 API providers); 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 $0.11 per million tokens for Gemma 3 27B IT versus $0.113 for Qwen3.5 9B (1× as much) and $0.15 for Mistral Small 3.2 (1.4× 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), Mistral Small 3.2 131.7 (#123 of 148) and Gemma 3 27B IT 130.0 (#125 of 148). Their confidence ranges do not overlap (136.5–141.3 vs 126.6–133.9), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, Mistral Small 3.2 49.1%, Gemma 3 27B IT 47.7%; OTIS Mock AIME 2024–2025 — Qwen3.5 9B 61.7%, Mistral Small 3.2 30.3%, Gemma 3 27B IT 22.5%.

Which is better for coding?

There are no published SWE-bench Verified results for Gemma 3 27B IT, 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?

Qwen3.5 9B has the largest context window at 262,144 tokens, against 131,072 for Gemma 3 27B IT and 128,000 for Mistral Small 3.2. Maximum output per response: Gemma 3 27B IT up to 131,072, Mistral Small 3.2 up to 16,384, Qwen3.5 9B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Gemma 3 27B IT 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?

Yes, all three publish their weights, so you can self-host them.

Which is newer?

Qwen3.5 9B is the newest, released Feb 23, 2026. Mistral Small 3.2 came out Jun 20, 2025; Gemma 3 27B IT came out Mar 12, 2025. Knowledge cutoff: Gemma 3 27B IT Aug 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

Related comparisons