Model Comparison

Qwen3.7-Plus vs Qwen3.7 MaxWhich is better in 2026?

Qwen3.7 Max significantly outperforms across most benchmarks. Qwen3.7-Plus is 3.3x cheaper per token.

Verdict: Qwen3.7-Plus vs Qwen3.7 Max — which is better?

Qwen3.7-Plus (by Alibaba Cloud / Qwen Team) and Qwen3.7 Max (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 3 benchmarks (IFEval, QwenWorldBench, Terminal-Bench 2.0), while Qwen3.7 Max is better at 32 benchmarks (BFCL-V4, Claw-Eval, CoWorkBench, CritPT, Finance Agent v2, GDPval-AA, Global PIQA, GPQA, HMMT Feb 26, Humanity's Last Exam, IMO-AnswerBench, Include, LiveCodeBench v6, MAXIFE, MCP Atlas, MCP-Mark, MMLU-Pro, MMLU-ProX, MMLU-Redux, MMMLU, NL2Repo, NOVA-63, PolyMATH, SciCode, SkillsBench, SpreadSheetBench-v1, SuperGPQA, SWE-bench Multilingual, SWE-Bench Pro, SWE-Bench Verified, VITA-Bench, WMT24++). Qwen3.7 Max significantly outperforms across most benchmarks.

On price, Qwen3.7-Plus is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Choose Qwen3.7-Plus if…

  • cost matters — it's about 3.3x cheaper per token
  • you want the most recent training data — it shipped May 2026

Choose Qwen3.7 Max if…

  • you want the strongest raw capability — it leads on 33 of 36 shared benchmarks

Performance Benchmarks

Comparative analysis across standard metrics

36 benchmarks

Qwen3.7-Plus outperforms in 3 benchmarks (IFEval, QwenWorldBench, Terminal-Bench 2.0), while Qwen3.7 Max is better at 32 benchmarks (BFCL-V4, Claw-Eval, CoWorkBench, CritPT, Finance Agent v2, GDPval-AA, Global PIQA, GPQA, HMMT Feb 26, Humanity's Last Exam, IMO-AnswerBench, Include, LiveCodeBench v6, MAXIFE, MCP Atlas, MCP-Mark, MMLU-Pro, MMLU-ProX, MMLU-Redux, MMMLU, NL2Repo, NOVA-63, PolyMATH, SciCode, SkillsBench, SpreadSheetBench-v1, SuperGPQA, SWE-bench Multilingual, SWE-Bench Pro, SWE-Bench Verified, VITA-Bench, WMT24++).

Qwen3.7 Max 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 3.9x cheaper than Qwen3.7 Max ($1.25/1M tokens).

For output processing, Qwen3.7-Plus ($1.28/1M tokens) is 2.9x cheaper than Qwen3.7 Max ($3.75/1M tokens).

In conclusion, Qwen3.7 Max 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
Qwen3.7 Max
Input tokens$1.25
Output tokens$3.75
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,000,000 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
Qwen3.7 Max
Input1,000,000 tokens
Output65,536 tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.7-Plus supports multimodal inputs, whereas Qwen3.7 Max does not.

Qwen3.7-Plus can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3.7-Plus

Text
Images
Audio
Video

Qwen3.7 Max

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Qwen3.7-Plus

Proprietary

Closed source

Qwen3.7 Max

Proprietary

Closed source

Release Timeline

When each model was launched

Qwen3.7-Plus was released on 2026-05-31, while Qwen3.7 Max was released on 2026-05-19.

Qwen3.7-Plus is 0 month newer than Qwen3.7 Max.

Qwen3.7-Plus

May 31, 2026

1 months ago

1w newer
Qwen3.7 Max

May 19, 2026

1 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. Qwen3.7 Max is available from Novita, Together.

Qwen3.7-Plus

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

Qwen3.7 Max

novita logo
Novita
Input Price:Input: $1.25/1MOutput Price:Output: $3.75/1M
together logo
Together
Input Price:Input: $2.50/1MOutput Price:Output: $7.50/1M
* 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

Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Higher IFEval score (94.6% vs 94.3%)
Higher QwenWorldBench score (62.1% vs 57.3%)
Higher Terminal-Bench 2.0 score (70.3% vs 69.7%)
Alibaba Cloud / Qwen Team

Qwen3.7 Max

View details

Alibaba Cloud / Qwen Team

Higher BFCL-V4 score (75.0% vs 72.9%)
Higher Claw-Eval score (65.2% vs 62.7%)
Higher CoWorkBench score (67.2% vs 65.1%)
Higher CritPT score (11.4% vs 6.0%)
Higher Finance Agent v2 score (48.4% vs 38.2%)
Higher GDPval-AA score (43.6% vs 31.5%)
Higher Global PIQA score (91.4% vs 90.3%)
Higher GPQA score (92.4% vs 90.3%)
Higher HMMT Feb 26 score (97.1% vs 92.9%)
Higher Humanity's Last Exam score (41.4% vs 34.7%)
Higher IMO-AnswerBench score (90.0% vs 86.0%)
Higher Include score (86.2% vs 83.0%)
Higher LiveCodeBench v6 score (91.6% vs 89.6%)
Higher MAXIFE score (89.2% vs 88.8%)
Higher MCP Atlas score (76.4% vs 73.2%)
Higher MCP-Mark score (60.8% vs 58.7%)
Higher MMLU-Pro score (89.6% vs 88.5%)
Higher MMLU-ProX score (87.0% vs 85.4%)
Higher MMLU-Redux score (95.0% vs 94.5%)
Higher MMMLU score (90.3% vs 89.0%)
Higher NL2Repo score (47.2% vs 41.1%)
Higher NOVA-63 score (59.0% vs 58.8%)
Higher PolyMATH score (86.5% vs 84.0%)
Higher SciCode score (53.5% vs 51.3%)
Higher SkillsBench score (59.2% vs 54.9%)
Higher SpreadSheetBench-v1 score (87.0% vs 86.3%)
Higher SuperGPQA score (73.6% vs 71.4%)
Higher SWE-bench Multilingual score (78.3% vs 75.8%)
Higher SWE-Bench Pro score (60.6% vs 57.6%)
Higher SWE-Bench Verified score (80.4% vs 77.7%)
Higher VITA-Bench score (47.9% vs 45.6%)
Higher WMT24++ score (85.8% vs 84.6%)

Detailed Comparison

Interactive Arena

Judge for yourself.

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

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

FAQ

Common questions about Qwen3.7-Plus vs Qwen3.7 Max.

Which is better, Qwen3.7-Plus or Qwen3.7 Max?

Qwen3.7 Max significantly outperforms across most benchmarks. Qwen3.7-Plus is made by Alibaba Cloud / Qwen Team and Qwen3.7 Max 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 Qwen3.7 Max 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%. Qwen3.7 Max scores HMMT Feb 26: 97.1%, Kernel Bench L3: 96.0%, MMLU-Redux: 95.0%, IFEval: 94.3%, GPQA: 92.4%.

Is Qwen3.7-Plus cheaper than Qwen3.7 Max?

Qwen3.7-Plus is 3.9x cheaper for input tokens. Qwen3.7-Plus costs $0.32/M input and $1.28/M output via together. Qwen3.7 Max costs $1.25/M input and $3.75/M output via novita.

What are the context window sizes for Qwen3.7-Plus and Qwen3.7 Max?

Qwen3.7-Plus supports 1.0M tokens and Qwen3.7 Max supports 1.0M 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 Qwen3.7 Max?

Key differences include input pricing ($0.32 vs $1.25/M), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

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