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Comparison · 3 models · Updated Nov 2, 2026

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

Qwen Flash comes out ahead, 69 to 61 and 57 on our weighted score, though GPT OSS 20B is 16% cheaper per token.

  1. Alibaba (Qwen)

    Qwen3 30B-A3B Instruct 2507

    Released Jul 28, 2025

    57/100
    • ECI137.3
    • Price$0.10 / $0.30
    • Context262K
  2. Our pick

    Alibaba (Qwen)

    Qwen Flash

    Released Jul 28, 2025

    69/100
    • ECI—
    • Price$0.05 / $0.40
    • Context1M
  3. OpenAI

    GPT OSS 20B

    Released Aug 5, 2025

    61/100
    • ECI137.8
    • Price$0.07 / $0.25
    • Context131K
01 — Verdict

Qwen Flash is our pick

Qwen Flash is the better all-round choice, scoring 69/100 against GPT OSS 20B (61) and Qwen3 30B-A3B Instruct 2507 (57). It leads on inputs & features and context window. GPT OSS 20B wins on price. 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 · Qwen Flash $0.138 · Qwen3 30B-A3B Instruct 2507 $0.15 per 1M tokens (3:1 blend)
  • Longest contextQwen FlashQwen Flash 1,000,000 · Qwen3 30B-A3B Instruct 2507 262,144 · GPT OSS 20B 131,072 tokens
  • Widest inputsSame inputsQwen3 30B-A3B Instruct 2507: Text · Qwen Flash: Text · GPT OSS 20B: Text
  • Self-hostingQwen3 30B-A3B Instruct 2507 and GPT OSS 20BPublishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightQwen3 30B-A3B Instruct 2507Qwen FlashGPT OSS 20B
Price50%858790
Inputs & features30%254535
Context window20%376025
Overall100%57/10069/10061/100

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.

Qwen3 30B-A3B Instruct 2507 vs Qwen Flash vs GPT OSS 20B specifications side by side
SpecificationQwen3 30B-A3B Instruct 2507Alibaba (Qwen)Qwen FlashAlibaba (Qwen)GPT OSS 20BOpenAI
Capability
Capabilities Index (ECI)137.3—137.8 (best)
ECI rank#124 of 165—#122 of 165 (best)
GPQA DiamondGraduate-level science questions55.6%—60.8% (best)
OTIS Mock AIME 2024–2025Competition mathematics62.2%—65.3% (best)
Price per million tokens
Input$0.10$0.05 (best)$0.07
Output$0.30$0.40$0.25 (best)
Cached input—$0.01—
Blended (3:1)$0.15$0.138$0.115 (best)
Long-context rateSame rateOver 256K: $0.25 / $2.00Same rate
Price sourceMedian of 12 providersOfficial Alibaba APIMedian of 37 providers
Limits
Context window262,144 tokens1,000,000 tokens (best)131,072 tokens
Max output16,384 tokens32,768 tokens (best)32,768 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenApache 2.0ProprietaryOpen
API model ID—qwen-flash—
API providers14641 (best)
ReleasedJul 28, 2025Jul 28, 2025Aug 5, 2025
Knowledge cutoff—Apr 2024Jun 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 30B-A3B Instruct 2507$1.60
  • Qwen Flash$1.30
  • GPT OSS 20B$1.20
04 — Questions

Which should you choose?

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

Qwen Flash is the better all-round choice, scoring 69/100 against GPT OSS 20B (61) and Qwen3 30B-A3B Instruct 2507 (57). It leads on inputs & features and context window. GPT OSS 20B wins on price. 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, Qwen3 30B-A3B Instruct 2507, Qwen Flash or GPT OSS 20B?

GPT OSS 20B is cheaper at $0.07 input / $0.25 output per million tokens (median across 37 API providers). Qwen Flash costs $0.05 input / $0.40 output per million tokens (official Alibaba API price); Qwen3 30B-A3B Instruct 2507 costs $0.10 input / $0.30 output per million tokens (median across 12 API providers). At a typical mix of three input tokens to one output token, that is $0.115 per million tokens for GPT OSS 20B versus $0.138 for Qwen Flash (1.2× as much) and $0.15 for Qwen3 30B-A3B Instruct 2507 (1.3× as much).

Which scores higher on benchmarks?

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

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 30B-A3B Instruct 2507, Qwen Flash and GPT OSS 20B 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?

Qwen 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: Qwen3 30B-A3B Instruct 2507 up to 16,384, Qwen Flash up to 32,768, GPT OSS 20B up to 32,768 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

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

Which is newer?

GPT OSS 20B is the newest, released Aug 5, 2025. Qwen3 30B-A3B Instruct 2507 came out Jul 28, 2025; Qwen Flash came out Jul 28, 2025. Knowledge cutoff: Qwen Flash Apr 2024, GPT OSS 20B Jun 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 Nov 2, 2026.