Model comparison
Qwen3.7-Plus vs GLM-5.1
- Input
- $0.40 / 1M tokens
- Output
- $1.20 / 1M tokens
- Context
- 1M
- Released
- 2026-06-02
- Input
- $1.40 / 1M tokens
- Output
- $4.40 / 1M tokens
- Context
- 200K
- Released
- 2026-04-07
Qwen3.7-Plus scores higher on 2 of the 3 benchmarks both models report (the other leads on 1); Qwen3.7-Plus is cheaper on input tokens ($0.4 vs $1.4 per 1M, 3.5×); Qwen3.7-Plus has the larger context window (1M vs 200K); GLM-5.1 ships open weights while Qwen3.7-Plus is API-only.
Specs and pricing side by side
| Spec | Qwen3.7-Plus | GLM-5.1 |
|---|---|---|
| Maker | Alibaba (Qwen) | Z.ai (Zhipu / GLM) |
| Released | 2026-06-02 | 2026-04-07 |
| Context window | 1M | 200K |
| Max output | 32,768 tokens | 128K |
| Input price | $0.40 / 1M tokens | $1.40 / 1M tokens |
| Output price | $1.20 / 1M tokens | $4.40 / 1M tokens |
| Parameters | Not disclosed | ~754B total, 40B active (MoE) |
| License | Proprietary (API-only) | MIT |
| Weights | API only | Open weights |
| Modalities | Text, Vision, Video | Text |
| Knowledge cutoff | Not disclosed | not published |
Benchmarks both models report
| Benchmark | Qwen3.7-Plus | GLM-5.1 |
|---|---|---|
| Terminal-Bench 2.0 | 70.3% | 63.5% |
| GPQA Diamond | 90.3% | 86.2% |
| Artificial Analysis Intelligence Index | 39index | 40index |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Qwen3.7-Plus if…
- You care about Terminal-Bench 2.0, GPQA Diamond (it scores higher on 2 shared benchmarks).
- Cost matters: input tokens cost 3.5× less ($0.4 vs $1.4 per 1M).
- You need the longer context (1M vs 200K).
- You need Vision / Video input, which GLM-5.1 lacks.
- Your use case is: computer-use and mobile agents that read screens and click the right UI element.
Pick GLM-5.1 if…
- You care about Artificial Analysis Intelligence Index (it scores higher on 1 shared benchmark).
- You want to self-host or fine-tune (open weights, MIT).
- Your use case is: long-running autonomous coding agents that plan, execute and self-correct over many iterations.
FAQ
Which is better, Qwen3.7-Plus or GLM-5.1?
Qwen3.7-Plus scores higher on 2 of the 3 benchmarks both models report (the other leads on 1); Qwen3.7-Plus is cheaper on input tokens ($0.4 vs $1.4 per 1M, 3.5×); Qwen3.7-Plus has the larger context window (1M vs 200K); GLM-5.1 ships open weights while Qwen3.7-Plus is API-only. The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Qwen3.7-Plus?
Qwen3.7-Plus: $0.40 / 1M tokens input, $1.20 / 1M tokens output. GLM-5.1: $1.40 / 1M tokens input, $4.40 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Qwen3.7-Plus and GLM-5.1?
Qwen3.7-Plus offers 1M with up to 32,768 tokens output; GLM-5.1 offers 200K with up to 128K output.
Is Qwen3.7-Plus newer than GLM-5.1?
Qwen3.7-Plus was released 2026-06-02; GLM-5.1 was released 2026-04-07.