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Comparison · 3 models · Updated Nov 2, 2026

GPT OSS 20B vs Qwen3 Coder Flash vs Qwen3 30B-A3B Instruct 2507

GPT OSS 20B comes out ahead, 61 to 57 and 51 on our weighted score, and it is the cheaper option too.

  1. Our pick

    OpenAI

    GPT OSS 20B

    Released Aug 5, 2025

    61/100
    • ECI137.8
    • Price$0.07 / $0.25
    • Context131K
    Full specs Remove GPT OSS 20B

  2. Alibaba (Qwen)

    Qwen3 Coder Flash

    Released Jul 28, 2025

    51/100
    • ECI—
    • Price$0.30 / $1.50
    • Context1M
    Full specs Remove Qwen3 Coder Flash

  3. Alibaba (Qwen)

    Qwen3 30B-A3B Instruct 2507

    Released Jul 28, 2025

    57/100
    • ECI137.3
    • Price$0.10 / $0.30
    • Context262K
    Full specs Remove Qwen3 30B-A3B Instruct 2507
01 — Verdict

GPT OSS 20B is our pick

GPT OSS 20B is the better all-round choice, scoring 61/100 against Qwen3 30B-A3B Instruct 2507 (57) and Qwen3 Coder Flash (51). It leads on price. Qwen3 Coder Flash wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceGPT OSS 20BGPT OSS 20B $0.115 · Qwen3 30B-A3B Instruct 2507 $0.15 · Qwen3 Coder Flash $0.60 per 1M tokens (3:1 blend)
  • Longest contextQwen3 Coder FlashQwen3 Coder Flash 1,000,000 · Qwen3 30B-A3B Instruct 2507 262,144 · GPT OSS 20B 131,072 tokens
  • Widest inputsSame inputsGPT OSS 20B: Text · Qwen3 Coder Flash: Text · Qwen3 30B-A3B Instruct 2507: Text
  • Self-hostingGPT OSS 20B and Qwen3 30B-A3B Instruct 2507Publishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightGPT OSS 20BQwen3 Coder FlashQwen3 30B-A3B Instruct 2507
Price50%905885
Inputs & features30%353525
Context window20%256037
Overall100%61/10051/10057/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

GPT OSS 20B vs Qwen3 Coder Flash vs Qwen3 30B-A3B Instruct 2507 specifications side by side
SpecificationGPT OSS 20BOpenAIQwen3 Coder FlashAlibaba (Qwen)Qwen3 30B-A3B Instruct 2507Alibaba (Qwen)
Capability
Capabilities Index (ECI)137.8 (best)—137.3
ECI rank#122 of 165 (best)—#124 of 165
GPQA DiamondGraduate-level science questions60.8% (best)—55.6%
OTIS Mock AIME 2024–2025Competition mathematics65.3% (best)—62.2%
Price per million tokens
Input$0.07 (best)$0.30$0.10
Output$0.25 (best)$1.50$0.30
Cached input—$0.06—
Blended (3:1)$0.115 (best)$0.60$0.15
Long-context rateSame rateOver 32K: $0.50 / $2.50Same rate
Price sourceMedian of 37 providersOfficial Alibaba APIMedian of 12 providers
Limits
Context window131,072 tokens1,000,000 tokens (best)262,144 tokens
Max output32,768 tokens65,536 tokens (best)16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryOpenApache 2.0
API model ID—qwen3-coder-flash—
API providers41 (best)1014
ReleasedAug 5, 2025Jul 28, 2025Jul 28, 2025
Knowledge cutoffJun 2024Apr 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.

  • GPT OSS 20B$1.20
  • Qwen3 Coder Flash$6.00
  • Qwen3 30B-A3B Instruct 2507$1.60
04 — Questions

Which should you choose?

Which is better: GPT OSS 20B, Qwen3 Coder Flash or Qwen3 30B-A3B Instruct 2507?

GPT OSS 20B is the better all-round choice, scoring 61/100 against Qwen3 30B-A3B Instruct 2507 (57) and Qwen3 Coder Flash (51). It leads on price. Qwen3 Coder Flash wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, GPT OSS 20B, Qwen3 Coder Flash or Qwen3 30B-A3B Instruct 2507?

GPT OSS 20B is cheaper at $0.07 input / $0.25 output per million tokens (median across 37 API providers). Qwen3 30B-A3B Instruct 2507 costs $0.10 input / $0.30 output per million tokens (median across 12 API providers); Qwen3 Coder Flash costs $0.30 input / $1.50 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.115 per million tokens for GPT OSS 20B versus $0.15 for Qwen3 30B-A3B Instruct 2507 (1.3× as much) and $0.60 for Qwen3 Coder Flash (5.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. GPT OSS 20B has an ECI of 137.8, Qwen3 Coder Flash has not been scored yet and Qwen3 30B-A3B Instruct 2507 has an ECI of 137.3.

Which is better for coding?

There are no published SWE-bench Verified results for GPT OSS 20B, Qwen3 Coder Flash and Qwen3 30B-A3B Instruct 2507 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen3 Coder Flash has the largest context window at 1,000,000 tokens, against 262,144 for Qwen3 30B-A3B Instruct 2507 and 131,072 for GPT OSS 20B. Maximum output per response: GPT OSS 20B up to 32,768, Qwen3 Coder Flash up to 65,536, Qwen3 30B-A3B Instruct 2507 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GPT OSS 20B accepts text; Qwen3 Coder Flash accepts text; Qwen3 30B-A3B Instruct 2507 accepts text. They handle the same number of input types.

Are any of these open source?

GPT OSS 20B and Qwen3 30B-A3B Instruct 2507 publishes its weights (Apache 2.0) and can be self-hosted; Qwen3 Coder Flash is proprietary.

Which is newer?

GPT OSS 20B is the newest, released Aug 5, 2025. Qwen3 Coder Flash came out Jul 28, 2025; Qwen3 30B-A3B Instruct 2507 came out Jul 28, 2025. Knowledge cutoff: GPT OSS 20B Jun 2024, Qwen3 Coder Flash Apr 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.

05 — Keep comparing

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