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Comparison · 3 models · Updated Oct 4, 2026

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

Qwen3.5 Flash comes out ahead, 75 to 70 and 69 on our weighted score, though GPT-5 Nano is 21% cheaper per token.

  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. Our pick

    Alibaba (Qwen)

    Qwen3.5 Flash

    Released Feb 23, 2026

    75/100
    • ECI144.0
    • Price$0.10 / $0.40
    • Context1M
    Full specs Remove Qwen3.5 Flash
01 — Verdict

Qwen3.5 Flash is our pick

Qwen3.5 Flash is the better all-round choice, scoring 75/100 against GPT-5 Nano (70) and Gemma 4 31B IT (69). It leads on capability, inputs & features and context window. GPT-5 Nano wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 FlashCapabilities Index (ECI): Qwen3.5 Flash 144.0 · Gemma 4 31B IT 142.8 · GPT-5 Nano 139.4
  • Lowest priceGPT-5 NanoGPT-5 Nano $0.138 · Qwen3.5 Flash $0.175 · Gemma 4 31B IT $0.205 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 FlashQwen3.5 Flash 1,000,000 · GPT-5 Nano 400,000 · Gemma 4 31B IT 262,144 tokens
  • Widest inputsQwen3.5 FlashGemma 4 31B IT: Text, Images · GPT-5 Nano: Text, Images · Qwen3.5 Flash: Text, Images, Video
  • Self-hostingGemma 4 31B ITPublishes downloadable weights
How the score is built
MeasureWeightGemma 4 31B ITGPT-5 NanoQwen3.5 Flash
CapabilityCapabilities Index (ECI)50%696571
Price25%839186
Inputs & features15%707080
Context window10%374460
Overall100%69/10070/10075/100
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 Flash specifications side by side
SpecificationGemma 4 31B ITGoogleGPT-5 NanoOpenAIQwen3.5 FlashAlibaba (Qwen)
Capability
Capabilities Index (ECI)142.8139.4144.0 (best)
ECI rank#86 of 148#102 of 148#82 of 148 (best)
GPQA DiamondGraduate-level science questions75.8%69.4%82.3% (best)
FrontierMath Tiers 1–3Research-level mathematics—20.0% (best)18.3%
OTIS Mock AIME 2024–2025Competition mathematics73.3%81.1%84.4% (best)
SimpleQA VerifiedShort factual questions10.4%11.7%20.3% (best)
Price per million tokens
Input$0.14$0.05 (best)$0.10
Output$0.40$0.40$0.40
Cached input—$0.005 (best)$0.01
Blended (3:1)$0.205$0.138 (best)$0.175
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 30 providersOfficial OpenAI APIOfficial Alibaba API
Limits
Context window262,144 tokens400,000 tokens1,000,000 tokens (best)
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
WeightsOpenProprietaryProprietary
API model IDgemma-4-31b-itgpt-5-nanoqwen3.5-flash
API providers38 (best)218
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 Flash$1.80
04 — Questions

Which should you choose?

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

Qwen3.5 Flash is the better all-round choice, scoring 75/100 against GPT-5 Nano (70) and Gemma 4 31B IT (69). It leads on capability, inputs & features and context window. GPT-5 Nano wins on price. 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 Flash?

GPT-5 Nano is cheaper at $0.05 input / $0.40 output per million tokens (official OpenAI API price). Qwen3.5 Flash costs $0.10 input / $0.40 output per million tokens (official Alibaba 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 $0.138 per million tokens for GPT-5 Nano versus $0.175 for Qwen3.5 Flash (1.3× as much) and $0.205 for Gemma 4 31B IT (1.5× as much).

Which scores higher on benchmarks?

Qwen3.5 Flash scores higher on the Capabilities Index (ECI): Qwen3.5 Flash 144.0 (#82 of 148), Gemma 4 31B IT 142.8 (#86 of 148) and GPT-5 Nano 139.4 (#102 of 148). The confidence ranges of the top two overlap (141.6–145.5 vs 140.3–144.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 Flash 82.3%, Gemma 4 31B IT 75.8%, GPT-5 Nano 69.4%; OTIS Mock AIME 2024–2025 — Qwen3.5 Flash 84.4%, GPT-5 Nano 81.1%, Gemma 4 31B IT 73.3%; SimpleQA Verified — Qwen3.5 Flash 20.3%, GPT-5 Nano 11.7%, Gemma 4 31B IT 10.4%.

Which is better for coding?

There are no published SWE-bench Verified results for Gemma 4 31B IT, GPT-5 Nano and Qwen3.5 Flash yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 Flash 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 Flash has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5 Nano and 262,144 for Gemma 4 31B IT. Maximum output per response: Gemma 4 31B IT up to 32,768, GPT-5 Nano up to 128,000, Qwen3.5 Flash 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 Flash accepts text, images and video. Qwen3.5 Flash handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Gemma 4 31B IT is the newest, released Apr 2, 2026. Qwen3.5 Flash 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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