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Comparison · 3 models · Updated Oct 4, 2026

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

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. 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

  2. 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

  3. OpenAI

    GPT-5 Nano

    Released Aug 7, 2025

    70/100
    • ECI139.4
    • Price$0.05 / $0.40
    • Context400K
    Full specs Remove GPT-5 Nano
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 · Qwen3.5 9B 262,144 · Gemma 4 31B IT 262,144 tokens
  • Widest inputsQwen3.5 9BQwen3.5 9B: Text, Images, Video · Gemma 4 31B IT: Text, Images · GPT-5 Nano: Text, Images
  • Self-hostingQwen3.5 9B and Gemma 4 31B ITPublishes downloadable weights
How the score is built
MeasureWeightQwen3.5 9BGemma 4 31B ITGPT-5 Nano
CapabilityCapabilities Index (ECI)50%656965
Price25%958391
Inputs & features15%807070
Context window10%373744
Overall100%72/10069/10070/100
02 — Side by side

Every spec in one table

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

Qwen3.5 9B vs Gemma 4 31B IT vs GPT-5 Nano specifications side by side
SpecificationQwen3.5 9BAlibaba (Qwen)Gemma 4 31B ITGoogleGPT-5 NanoOpenAI
Capability
Capabilities Index (ECI)139.5142.8 (best)139.4
ECI rank#101 of 148#86 of 148 (best)#102 of 148
GPQA DiamondGraduate-level science questions79.0% (best)75.8%69.4%
FrontierMath Tiers 1–3Research-level mathematics——20.0%
OTIS Mock AIME 2024–2025Competition mathematics61.7%73.3%81.1% (best)
SimpleQA VerifiedShort factual questions—10.4%11.7% (best)
Price per million tokens
Input$0.10$0.14$0.05 (best)
Output$0.15 (best)$0.40$0.40
Cached input——$0.005
Blended (3:1)$0.113 (best)$0.205$0.138
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 14 providersMedian of 30 providersOfficial OpenAI API
Limits
Context window262,144 tokens262,144 tokens400,000 tokens (best)
Max output65,536 tokens32,768 tokens128,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoYesNoNo
ReasoningYesYesYesminimal · low · medium · high
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsOpenOpenProprietary
API model ID—gemma-4-31b-itgpt-5-nano
API providers1538 (best)21
ReleasedFeb 23, 2026Apr 2, 2026Aug 7, 2025
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.

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

Which should you choose?

Which is better: Qwen3.5 9B, Gemma 4 31B IT or GPT-5 Nano?

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, Qwen3.5 9B, Gemma 4 31B IT or GPT-5 Nano?

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 Qwen3.5 9B, Gemma 4 31B IT and GPT-5 Nano 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 Qwen3.5 9B and 262,144 for Gemma 4 31B IT. Maximum output per response: Qwen3.5 9B up to 65,536, Gemma 4 31B IT up to 32,768, GPT-5 Nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Qwen3.5 9B accepts text, images and video; Gemma 4 31B IT accepts text and images; GPT-5 Nano accepts text and images. Qwen3.5 9B handles the widest range of inputs.

Are any of these open source?

Qwen3.5 9B and Gemma 4 31B IT 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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