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Comparison · 3 models · Updated Oct 4, 2026

Gemma 4 31B IT vs GPT-5 Nano vs Qwen3.5 9B

Too close to call on our weighted score (Qwen3.5 9B 72, GPT-5 Nano 70, Gemma 4 31B IT 69). The right pick depends on what you value most.

  1. Google

    Gemma 4 31B IT

    Released Apr 2, 2026

    69/100
    • ECI142.8
    • Price$0.14 / $0.40
    • Context262K
    Full specs Remove Gemma 4 31B IT

  2. 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. 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, Gemma 4 31B IT 69/100), so choose by what matters most for your work: Gemma 4 31B IT for raw capability, Qwen3.5 9B on price and GPT-5 Nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemma 4 31B ITCapabilities Index (ECI): Gemma 4 31B IT 142.8 · Qwen3.5 9B 139.5 · GPT-5 Nano 139.4
  • Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · GPT-5 Nano $0.138 · Gemma 4 31B IT $0.205 per 1M tokens (3:1 blend)
  • Longest contextGPT-5 NanoGPT-5 Nano 400,000 · Gemma 4 31B IT 262,144 · Qwen3.5 9B 262,144 tokens
  • Widest inputsQwen3.5 9BGemma 4 31B IT: Text, Images · GPT-5 Nano: Text, Images · Qwen3.5 9B: Text, Images, Video
  • Self-hostingGemma 4 31B IT and Qwen3.5 9BPublishes downloadable weights
How the score is built
MeasureWeightGemma 4 31B ITGPT-5 NanoQwen3.5 9B
CapabilityCapabilities Index (ECI)50%696565
Price25%839195
Inputs & features15%707080
Context window10%374437
Overall100%69/10070/10072/100
02 — Side by side

Every spec in one table

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

Gemma 4 31B IT vs GPT-5 Nano vs Qwen3.5 9B specifications side by side
SpecificationGemma 4 31B ITGoogleGPT-5 NanoOpenAIQwen3.5 9BAlibaba (Qwen)
Capability
Capabilities Index (ECI)142.8 (best)139.4139.5
ECI rank#86 of 148 (best)#102 of 148#101 of 148
GPQA DiamondGraduate-level science questions75.8%69.4%79.0% (best)
FrontierMath Tiers 1–3Research-level mathematics—20.0%—
OTIS Mock AIME 2024–2025Competition mathematics73.3%81.1% (best)61.7%
SimpleQA VerifiedShort factual questions10.4%11.7% (best)—
Price per million tokens
Input$0.14$0.05 (best)$0.10
Output$0.40$0.40$0.15 (best)
Cached input—$0.005—
Blended (3:1)$0.205$0.138$0.113 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 30 providersOfficial OpenAI APIMedian of 14 providers
Limits
Context window262,144 tokens400,000 tokens (best)262,144 tokens
Max output32,768 tokens128,000 tokens (best)65,536 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningYesYesminimal · low · medium · highYes
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsOpenProprietaryOpen
API model IDgemma-4-31b-itgpt-5-nano—
API providers38 (best)2115
ReleasedApr 2, 2026Aug 7, 2025Feb 23, 2026
Knowledge cutoff—May 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.

  • Gemma 4 31B IT$2.20
  • GPT-5 Nano$1.30
  • Qwen3.5 9B$1.30
04 — Questions

Which should you choose?

Which is better: Gemma 4 31B IT, GPT-5 Nano 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, Gemma 4 31B IT 69/100), so choose by what matters most for your work: Gemma 4 31B IT for raw capability, Qwen3.5 9B on price and GPT-5 Nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemma 4 31B IT, GPT-5 Nano 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); Gemma 4 31B IT costs $0.14 input / $0.40 output per million tokens (median across 30 API providers). 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 $0.205 for Gemma 4 31B IT (1.8× as much).

Which scores higher on benchmarks?

Gemma 4 31B IT scores higher on the Capabilities Index (ECI): Gemma 4 31B IT 142.8 (#86 of 148), Qwen3.5 9B 139.5 (#101 of 148) and GPT-5 Nano 139.4 (#102 of 148). The confidence ranges of the top two overlap (140.3–144.9 vs 136.5–141.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, Gemma 4 31B IT 75.8%, GPT-5 Nano 69.4%; OTIS Mock AIME 2024–2025 — GPT-5 Nano 81.1%, Gemma 4 31B IT 73.3%, Qwen3.5 9B 61.7%.

Which is better for coding?

There are no published SWE-bench Verified results for Gemma 4 31B IT, GPT-5 Nano and Qwen3.5 9B yet, so there is no like-for-like coding score. On overall capability, Gemma 4 31B IT 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 Gemma 4 31B IT and 262,144 for Qwen3.5 9B. Maximum output per response: Gemma 4 31B IT up to 32,768, GPT-5 Nano up to 128,000, Qwen3.5 9B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Gemma 4 31B IT accepts text and images; GPT-5 Nano 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?

Gemma 4 31B IT and Qwen3.5 9B publishes its weights and can be self-hosted; GPT-5 Nano is proprietary.

Which is newer?

Gemma 4 31B IT is the newest, released Apr 2, 2026. Qwen3.5 9B came out Feb 23, 2026; GPT-5 Nano came out Aug 7, 2025. Knowledge cutoff: 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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