Model Comparison

Qwen3.7-Plus vs Qwen3.6-27BWhich is better in 2026?

Qwen3.7-Plus significantly outperforms across most benchmarks. Qwen3.7-Plus is 2.4x cheaper per token.

Verdict: Qwen3.7-Plus vs Qwen3.6-27B — which is better?

Qwen3.7-Plus (by Alibaba Cloud / Qwen Team) and Qwen3.6-27B (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Qwen3.7-Plus outperforms in 23 benchmarks (AndroidWorld, CharXiv-R, Claw-Eval, ERQA, GPQA, HMMT Feb 26, Humanity's Last Exam, IMO-AnswerBench, LiveCodeBench v6, MLVU, MMLU-Pro, MMLU-Redux, MMMU-Pro, NL2Repo, RealWorldQA, SimpleVQA, SkillsBench, SuperGPQA, SWE-bench Multilingual, SWE-Bench Pro, SWE-Bench Verified, Terminal-Bench 2.0, VideoMMMU), while Qwen3.6-27B is better at 1 benchmark (GDPval-AA). Qwen3.7-Plus significantly outperforms across most benchmarks.

On price, Qwen3.7-Plus is roughly 2.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3.7-Plus also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose Qwen3.7-Plus if…

  • you want the strongest raw capability — it leads on 23 of 24 shared benchmarks
  • cost matters — it's about 2.4x cheaper per token
  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped May 2026

Choose Qwen3.6-27B if…

  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

24 benchmarks

Qwen3.7-Plus outperforms in 23 benchmarks (AndroidWorld, CharXiv-R, Claw-Eval, ERQA, GPQA, HMMT Feb 26, Humanity's Last Exam, IMO-AnswerBench, LiveCodeBench v6, MLVU, MMLU-Pro, MMLU-Redux, MMMU-Pro, NL2Repo, RealWorldQA, SimpleVQA, SkillsBench, SuperGPQA, SWE-bench Multilingual, SWE-Bench Pro, SWE-Bench Verified, Terminal-Bench 2.0, VideoMMMU), while Qwen3.6-27B is better at 1 benchmark (GDPval-AA).

Qwen3.7-Plus significantly outperforms across most benchmarks.

Fri Jul 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3.7-Plus costs less

For input processing, Qwen3.7-Plus ($0.32/1M tokens) is 1.9x cheaper than Qwen3.6-27B ($0.60/1M tokens).

For output processing, Qwen3.7-Plus ($1.28/1M tokens) is 2.8x cheaper than Qwen3.6-27B ($3.60/1M tokens).

In conclusion, Qwen3.6-27B is more expensive than Qwen3.7-Plus.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Jul 17 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3.7-Plus
Input tokens$0.32
Output tokens$1.28
Best providerTogether
Alibaba Cloud / Qwen Team
Qwen3.6-27B
Input tokens$0.60
Output tokens$3.60
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Qwen3.7-Plus accepts 1,000,000 input tokens compared to Qwen3.6-27B's 262,144 tokens. Both models can generate responses up to 65,536 tokens.

Alibaba Cloud / Qwen Team
Qwen3.7-Plus
Input1,000,000 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
Qwen3.6-27B
Input262,144 tokens
Output65,536 tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen3.7-Plus and Qwen3.6-27B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Qwen3.7-Plus

Text
Images
Audio
Video

Qwen3.6-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen3.7-Plus is licensed under a proprietary license, while Qwen3.6-27B uses Apache 2.0.

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

Qwen3.7-Plus

Proprietary

Closed source

Qwen3.6-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3.7-Plus was released on 2026-05-31, while Qwen3.6-27B was released on 2026-04-21.

Qwen3.7-Plus is 1 month newer than Qwen3.6-27B.

Qwen3.7-Plus

May 31, 2026

1 months ago

1mo newer
Qwen3.6-27B

Apr 21, 2026

2 months ago

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

Provider Availability

Qwen3.7-Plus is available from Together. Qwen3.6-27B is available from Novita.

Qwen3.7-Plus

together logo
Together
Input Price:Input: $0.32/1MOutput Price:Output: $1.28/1M

Qwen3.6-27B

novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $3.60/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Alibaba Cloud / Qwen Team

Qwen3.7-Plus

View details

Alibaba Cloud / Qwen Team

Larger context window (1,000,000 tokens)
Less expensive input tokens
Less expensive output tokens
Higher AndroidWorld score (81.0% vs 70.3%)
Higher CharXiv-R score (85.9% vs 78.4%)
Higher Claw-Eval score (62.7% vs 60.6%)
Higher ERQA score (69.8% vs 62.5%)
Higher GPQA score (90.3% vs 87.8%)
Higher HMMT Feb 26 score (92.9% vs 84.3%)
Higher Humanity's Last Exam score (34.7% vs 24.0%)
Higher IMO-AnswerBench score (86.0% vs 80.8%)
Higher LiveCodeBench v6 score (89.6% vs 83.9%)
Higher MLVU score (87.4% vs 86.6%)
Higher MMLU-Pro score (88.5% vs 86.2%)
Higher MMLU-Redux score (94.5% vs 93.5%)
Higher MMMU-Pro score (79.0% vs 75.8%)
Higher NL2Repo score (41.1% vs 36.2%)
Higher RealWorldQA score (86.9% vs 84.1%)
Higher SimpleVQA score (81.7% vs 56.1%)
Higher SkillsBench score (54.9% vs 48.2%)
Higher SuperGPQA score (71.4% vs 66.0%)
Higher SWE-bench Multilingual score (75.8% vs 71.3%)
Higher SWE-Bench Pro score (57.6% vs 53.5%)
Higher SWE-Bench Verified score (77.7% vs 77.2%)
Higher Terminal-Bench 2.0 score (70.3% vs 59.3%)
Higher VideoMMMU score (85.4% vs 84.4%)
Alibaba Cloud / Qwen Team

Qwen3.6-27B

View details

Alibaba Cloud / Qwen Team

Has open weights
Higher GDPval-AA score (38.6% vs 31.5%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Qwen3.7-Plus and Qwen3.6-27B side-by-side, then vote on the output you prefer.

Qwen3.7-Plus
✓ Preferred
Qwen3.6-27B
Open in Playground
AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3.7-Plus
Alibaba Cloud / Qwen Team
Qwen3.6-27B

FAQ

Common questions about Qwen3.7-Plus vs Qwen3.6-27B.

Which is better, Qwen3.7-Plus or Qwen3.6-27B?

Qwen3.7-Plus significantly outperforms across most benchmarks. Qwen3.7-Plus is made by Alibaba Cloud / Qwen Team and Qwen3.6-27B 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 Qwen3.7-Plus compare to Qwen3.6-27B in benchmarks?

Qwen3.7-Plus scores IFEval: 94.6%, MMLU-Redux: 94.5%, HMMT Feb 26: 92.9%, MRCR v2: 91.7%, OmniDocBench 1.5: 91.4%. Qwen3.6-27B scores CountBench: 97.8%, VLMsAreBlind: 97.0%, V*: 94.7%, AIME 2026: 94.1%, HMMT 2025: 93.8%.

Is Qwen3.7-Plus cheaper than Qwen3.6-27B?

Qwen3.7-Plus is 1.9x cheaper for input tokens. Qwen3.7-Plus costs $0.32/M input and $1.28/M output via together. Qwen3.6-27B costs $0.60/M input and $3.60/M output via novita.

What are the context window sizes for Qwen3.7-Plus and Qwen3.6-27B?

Qwen3.7-Plus supports 1.0M tokens and Qwen3.6-27B supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen3.7-Plus and Qwen3.6-27B?

Key differences include context window (1.0M vs 262K), input pricing ($0.32 vs $0.60/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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