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GPT OSS 20B vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 17.4.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 50.5 to 17.4, ranking #14 overall.

In the 2 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT OSS 20B

  • you want predictable pricing at $0.05/M input and $0.20/M output

Choose Qwen3.8-Flash-Next

  • overall performance matters — it scores 50.5 and ranks #14 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

GPT OSS 20B
OpenAI
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
17.4
#197
50.5
#14
Reasoning
15.9
#201
50.6
#12
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$0.05 / M
— / M
Output price
$0.20 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT OSS 20B
Qwen3.8-Flash-Next
Math
17.4#184
33.3#50
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

7 reported for GPT OSS 20B · 22 for Qwen3.8-Flash-Next

2 shared

GPT OSS 20B outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 2 benchmarks (GPQA, Humanity's Last Exam).

Qwen3.8-Flash-Next significantly outperforms across most benchmarks.

Sat Aug 29 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

104.1B diff

Qwen3.8-Flash-Next has 104.1B more parameters than GPT OSS 20B, making it 498.1% larger.

OpenAI
GPT OSS 20B
20.9Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
20.9B
GPT OSS 20B
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only GPT OSS 20B specifies input context (131,072 tokens). Only GPT OSS 20B specifies output context (32,768 tokens).

OpenAI
GPT OSS 20B
Input131,072 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Sat Aug 29 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8-Flash-Next supports multimodal inputs, whereas GPT OSS 20B does not.

Qwen3.8-Flash-Next can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT OSS 20B

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

GPT OSS 20B is licensed under Apache 2.0, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.

License differences may affect how you can use these models in commercial or open-source projects.

GPT OSS 20B

Apache 2.0

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

GPT OSS 20B was released on 2025-08-05, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 13 months newer than GPT OSS 20B.

GPT OSS 20B

Aug 5, 2025

1.1 years ago

Qwen3.8-Flash-Next

Aug 26, 2026

2 days ago

1.1yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GPT OSS 20B and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

GPT OSS 20B
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about GPT OSS 20B vs Qwen3.8-Flash-Next.

Which is better, GPT OSS 20B or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 17.4. GPT OSS 20B is made by OpenAI and Qwen3.8-Flash-Next is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT OSS 20B compare to Qwen3.8-Flash-Next in benchmarks?

GPT OSS 20B scores MMLU: 85.3%, CodeForces: 74.3%, GPQA: 71.5%, TAU-bench Retail: 54.8%, HealthBench: 42.5%. Qwen3.8-Flash-Next scores MathVision: 95.7%, LiveCodeBench v6: 91.9%, GPQA: 91.7%, CharXiv-R: 90.6%, RealWorldQA: 88.5%.

What are the context window sizes for GPT OSS 20B and Qwen3.8-Flash-Next?

GPT OSS 20B supports 131K tokens and Qwen3.8-Flash-Next supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT OSS 20B and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (17.4 vs 50.5), multimodal support (no vs yes), licensing (Apache 2.0 vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT OSS 20B and Qwen3.8-Flash-Next?

GPT OSS 20B is developed by OpenAI and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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