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Qwen3-235B-A22B-Instruct-2507 vs Qwen3.8-27B

Qwen3.8-27B significantly outperforms across most benchmarks.

Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3-235B-A22B-Instruct-2507 outperforms in 0 benchmarks, while Qwen3.8-27B is better at 2 benchmarks (GPQA, LiveCodeBench v6). Qwen3.8-27B significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Qwen3-235B-A22B-Instruct-2507

  • you want predictable pricing at $0.15/M input and $0.80/M output

Choose Qwen3.8-27B

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
0 of 2
2 of 2
Input price
$0.15 / M
— / M
Output price
$0.80 / M
— / M
Context window
262,144
Released
Jul 2025
Aug 2026
License
Apache 2.0
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Qwen3-235B-A22B-Instruct-2507 outperforms in 0 benchmarks, while Qwen3.8-27B is better at 2 benchmarks (GPQA, LiveCodeBench v6).

Qwen3.8-27B significantly outperforms across most benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

207.2B diff

Qwen3-235B-A22B-Instruct-2507 has 207.2B more parameters than Qwen3.8-27B, making it 745.9% larger.

Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
235.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
235.0B
Qwen3-235B-A22B-Instruct-2507
27.8B
Qwen3.8-27B

Context Window

Maximum input and output token capacity

Only Qwen3-235B-A22B-Instruct-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Instruct-2507 specifies output context (131,072 tokens).

Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.8-27B supports multimodal inputs, whereas Qwen3-235B-A22B-Instruct-2507 does not.

Qwen3.8-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3-235B-A22B-Instruct-2507

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 13 months newer than Qwen3-235B-A22B-Instruct-2507.

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

1.1 years ago

Qwen3.8-27B

Aug 14, 2026

1 weeks 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 Qwen3-235B-A22B-Instruct-2507 and Qwen3.8-27B side-by-side, then vote on the output you prefer.

Qwen3-235B-A22B-Instruct-2507
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about Qwen3-235B-A22B-Instruct-2507 vs Qwen3.8-27B.

Which is better, Qwen3-235B-A22B-Instruct-2507 or Qwen3.8-27B?

Qwen3.8-27B significantly outperforms across most benchmarks. Qwen3-235B-A22B-Instruct-2507 is made by Alibaba Cloud / Qwen Team and Qwen3.8-27B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen3-235B-A22B-Instruct-2507 compare to Qwen3.8-27B in benchmarks?

Qwen3-235B-A22B-Instruct-2507 scores ZebraLogic: 95.0%, MMLU-Redux: 93.1%, IFEval: 88.7%, MultiPL-E: 87.9%, Creative Writing v3: 87.5%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the context window sizes for Qwen3-235B-A22B-Instruct-2507 and Qwen3.8-27B?

Qwen3-235B-A22B-Instruct-2507 supports 262K tokens and Qwen3.8-27B 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 Qwen3-235B-A22B-Instruct-2507 and Qwen3.8-27B?

Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.