GLM-5.1 vs Qwen3.5 397B-A17B vs Qwen3.6 Max Preview
Qwen3.5 397B-A17B comes out ahead, 65 to 57 and 54 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
- Our pick
Alibaba (Qwen)Qwen3.5 397B-A17B
65/100- ECI146.7
- Price$0.60 / $3.60
- Context262K
- Alibaba (Qwen)
Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
Qwen3.5 397B-A17B is our pick
Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against GLM-5.1 (57) and Qwen3.6 Max Preview (54). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · Qwen3.6 Max Preview 149.2 · Qwen3.5 397B-A17B 146.7
- Lowest priceQwen3.5 397B-A17BQwen3.5 397B-A17B $1.35 · GLM-5.1 $2.15 · Qwen3.6 Max Preview $2.92 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 397B-A17B and Qwen3.6 Max PreviewQwen3.5 397B-A17B 262,144 · Qwen3.6 Max Preview 262,144 · GLM-5.1 200,000 tokens
- Widest inputsQwen3.5 397B-A17BGLM-5.1: Text · Qwen3.5 397B-A17B: Text, Images, Audio, Video · Qwen3.6 Max Preview: Text
- Self-hostingGLM-5.1 and Qwen3.5 397B-A17BPublishes downloadable weights
| Measure | Weight | GLM-5.1 | Qwen3.5 397B-A17B | Qwen3.6 Max Preview |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 74 | 77 |
| Price | 25% | 34 | 44 | 28 |
| Inputs & features | 15% | 45 | 90 | 35 |
| Context window | 10% | 32 | 37 | 37 |
| Overall | 100% | 57/100 | 65/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.1Z.ai (Zhipu) | Qwen3.5 397B-A17BAlibaba (Qwen) | Qwen3.6 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.9 (best) | 146.7 | 149.2 |
| ECI rank | #51 of 148 (best) | #67 of 148 | #54 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | 86.4% | 87.4% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% (best) | 31.2% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% (best) | 88.9% | 91.1% |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% | — | 76.7% (best) |
| SimpleQA VerifiedShort factual questions | 34.0% | — | 52.0% (best) |
| Price per million tokens | |||
| Input | $1.40 | $0.60 (best) | $1.30 |
| Output | $4.40 | $3.60 (best) | $7.80 |
| Cached input | $0.26 | — | $0.13 (best) |
| Blended (3:1) | $2.15 | $1.35 (best) | $2.92 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 200,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 65,536 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-5.1 | qwen3.5-397b-a17b | qwen3.6-max-preview |
| API providers | 40 (best) | 23 | 10 |
| Released | Apr 7, 2026 | Feb 15, 2026 | Apr 20, 2026 |
| Knowledge cutoff | — | — | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5.1$22.80
- Qwen3.5 397B-A17B$13.20
- Qwen3.6 Max Preview$28.60
Which should you choose?
Which is better: GLM-5.1, Qwen3.5 397B-A17B or Qwen3.6 Max Preview?
Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against GLM-5.1 (57) and Qwen3.6 Max Preview (54). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1, Qwen3.5 397B-A17B or Qwen3.6 Max Preview?
Qwen3.5 397B-A17B is cheaper at $0.60 input / $3.60 output per million tokens (official Alibaba API price). GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price); Qwen3.6 Max Preview costs $1.30 input / $7.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.35 per million tokens for Qwen3.5 397B-A17B versus $2.15 for GLM-5.1 (1.6× as much) and $2.92 for Qwen3.6 Max Preview (2.2× as much).
Which scores higher on benchmarks?
GLM-5.1 scores higher on the Capabilities Index (ECI): GLM-5.1 149.9 (#51 of 148), Qwen3.6 Max Preview 149.2 (#54 of 148) and Qwen3.5 397B-A17B 146.7 (#67 of 148). The confidence ranges of the top two overlap (148.0–151.6 vs 147.6–152.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, Qwen3.6 Max Preview 87.4%, Qwen3.5 397B-A17B 86.4%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, Qwen3.6 Max Preview 91.1%, Qwen3.5 397B-A17B 88.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 397B-A17B yet, so there is no like-for-like coding score. On overall capability, GLM-5.1 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.5 397B-A17B and Qwen3.6 Max Preview have the largest context windows (262,144 and 262,144 tokens), against 200,000 for GLM-5.1. Maximum output per response: GLM-5.1 up to 131,072, Qwen3.5 397B-A17B up to 65,536, Qwen3.6 Max Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; Qwen3.5 397B-A17B accepts text, images, audio and video; Qwen3.6 Max Preview accepts text. Qwen3.5 397B-A17B handles the widest range of inputs.
Are any of these open source?
GLM-5.1 and Qwen3.5 397B-A17B publishes its weights and can be self-hosted; Qwen3.6 Max Preview is proprietary.
Which is newer?
Qwen3.6 Max Preview is the newest, released Apr 20, 2026. GLM-5.1 came out Apr 7, 2026; Qwen3.5 397B-A17B came out Feb 15, 2026. Knowledge cutoff: Qwen3.6 Max Preview Apr 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
