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Comparison · 3 models · Updated Nov 2, 2026

Qwen3.5 Flash vs GPT OSS 120B vs Gemma 4 31B IT

Qwen3.5 Flash comes out ahead, 73 to 68 and 58 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen3.5 Flash

    Released Feb 23, 2026

    73/100
    • ECI143.6
    • Price$0.10 / $0.40
    • Context1M
  2. OpenAI

    GPT OSS 120B

    Released Aug 5, 2025

    58/100
    • ECI139.8
    • Price$0.15 / $0.60
    • Context131K
  3. Google

    Gemma 4 31B IT

    Released Apr 2, 2026

    68/100
    • ECI143.1
    • Price$0.14 / $0.40
    • Context262K
01 — Verdict

Qwen3.5 Flash is our pick

Qwen3.5 Flash is the better all-round choice, scoring 73/100 against Gemma 4 31B IT (68) and GPT OSS 120B (58). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 FlashCapabilities Index (ECI): Qwen3.5 Flash 143.6 · Gemma 4 31B IT 143.1 · GPT OSS 120B 139.8
  • Lowest priceQwen3.5 FlashQwen3.5 Flash $0.175 · Gemma 4 31B IT $0.205 · GPT OSS 120B $0.263 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 FlashQwen3.5 Flash 1,000,000 · Gemma 4 31B IT 262,144 · GPT OSS 120B 131,072 tokens
  • Widest inputsQwen3.5 FlashQwen3.5 Flash: Text, Images, Video · GPT OSS 120B: Text · Gemma 4 31B IT: Text, Images
  • Self-hostingGPT OSS 120B and Gemma 4 31B ITPublishes downloadable weights
How the score is built
MeasureWeightQwen3.5 FlashGPT OSS 120BGemma 4 31B IT
CapabilityCapabilities Index (ECI)50%696468
Price25%827479
Inputs & features15%803570
Context window10%602537
Overall100%73/10058/10068/100
02 — Side by side

Every spec in one table

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

Qwen3.5 Flash vs GPT OSS 120B vs Gemma 4 31B IT specifications side by side
SpecificationQwen3.5 FlashAlibaba (Qwen)GPT OSS 120BOpenAIGemma 4 31B ITGoogle
Capability
Capabilities Index (ECI)143.6 (best)139.8143.1
ECI rank#95 of 165 (best)#114 of 165#96 of 165
GPQA DiamondGraduate-level science questions82.3% (best)75.8%75.8%
FrontierMath Tiers 1–3Research-level mathematics18.3%——
OTIS Mock AIME 2024–2025Competition mathematics84.4%88.9% (best)73.3%
SimpleQA VerifiedShort factual questions20.3% (best)—10.4%
Price per million tokens
Input$0.10 (best)$0.15$0.14
Output$0.40 (best)$0.60$0.40 (best)
Cached input$0.01——
Blended (3:1)$0.175 (best)$0.263$0.205
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 65 providersMedian of 36 providers
Limits
Context window1,000,000 tokens (best)131,072 tokens262,144 tokens
Max output65,536 tokens (best)32,768 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoNo
AudioNoNoNo
VideoYesNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputYesNoYes
Availability
WeightsProprietaryOpenOpen
API model IDqwen3.5-flash—gemma-4-31b-it
API providers967 (best)46
ReleasedFeb 23, 2026Aug 5, 2025Apr 2, 2026
Knowledge cutoff—Jun 2024Jan 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.

  • Qwen3.5 Flash$1.80
  • GPT OSS 120B$2.70
  • Gemma 4 31B IT$2.20
04 — Questions

Which should you choose?

Which is better: Qwen3.5 Flash, GPT OSS 120B or Gemma 4 31B IT?

Qwen3.5 Flash is the better all-round choice, scoring 73/100 against Gemma 4 31B IT (68) and GPT OSS 120B (58). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3.5 Flash, GPT OSS 120B or Gemma 4 31B IT?

Qwen3.5 Flash is cheaper at $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 36 API providers); GPT OSS 120B costs $0.15 input / $0.60 output per million tokens (median across 65 API providers). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Qwen3.5 Flash versus $0.205 for Gemma 4 31B IT (1.2× as much) and $0.263 for GPT OSS 120B (1.5× as much).

Which scores higher on benchmarks?

Qwen3.5 Flash scores higher on the Capabilities Index (ECI): Qwen3.5 Flash 143.6 (#95 of 165), Gemma 4 31B IT 143.1 (#96 of 165) and GPT OSS 120B 139.8 (#114 of 165). The confidence ranges of the top two overlap (141.4–145.0 vs 140.8–145.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 Flash 82.3%, GPT OSS 120B 75.8%, Gemma 4 31B IT 75.8%; OTIS Mock AIME 2024–2025 — GPT OSS 120B 88.9%, Qwen3.5 Flash 84.4%, Gemma 4 31B IT 73.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 Flash, GPT OSS 120B and Gemma 4 31B IT 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 262,144 for Gemma 4 31B IT and 131,072 for GPT OSS 120B. Maximum output per response: Qwen3.5 Flash up to 65,536, GPT OSS 120B up to 32,768, Gemma 4 31B IT up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Qwen3.5 Flash accepts text, images and video; GPT OSS 120B accepts text; Gemma 4 31B IT accepts text and images. Qwen3.5 Flash handles the widest range of inputs.

Are any of these open source?

GPT OSS 120B and Gemma 4 31B IT publishes its weights and can be self-hosted; 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 OSS 120B came out Aug 5, 2025. Knowledge cutoff: GPT OSS 120B Jun 2024, Gemma 4 31B IT Jan 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 Nov 2, 2026.