GLM-5.1 vs Qwen3.6 Max Preview vs Qwen3.8 27B
Qwen3.8 27B comes out ahead, 67 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
Alibaba (Qwen)Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
- Our pickAlibaba (Qwen)
Qwen3.8 27B
67/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
Qwen3.8 27B is our pick
Qwen3.8 27B is the better all-round choice, scoring 67/100 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 · Qwen3.8 27B 149.4 · Qwen3.6 Max Preview 149.2
- Lowest priceQwen3.8 27BQwen3.8 27B $0.925 · GLM-5.1 $2.15 · Qwen3.6 Max Preview $2.92 per 1M tokens (3:1 blend)
- Longest contextQwen3.6 Max Preview and Qwen3.8 27BQwen3.6 Max Preview 262,144 · Qwen3.8 27B 262,144 · GLM-5.1 200,000 tokens
- Widest inputsQwen3.8 27BGLM-5.1: Text · Qwen3.6 Max Preview: Text · Qwen3.8 27B: Text, Images, Video
- Self-hostingGLM-5.1 and Qwen3.8 27BPublishes downloadable weights
| Measure | Weight | GLM-5.1 | Qwen3.6 Max Preview | Qwen3.8 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 77 | 77 |
| Price | 25% | 34 | 28 | 51 |
| Inputs & features | 15% | 45 | 35 | 80 |
| Context window | 10% | 32 | 37 | 37 |
| Overall | 100% | 57/100 | 54/100 | 67/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.1Z.ai (Zhipu) | Qwen3.6 Max PreviewAlibaba (Qwen) | Qwen3.8 27BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.9 (best) | 149.2 | 149.4 |
| ECI rank | #51 of 148 (best) | #54 of 148 | #53 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | 87.4% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% (best) | 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 | $1.30 | $0.40 (best) |
| Output | $4.40 | $7.80 | $2.50 (best) |
| Cached input | $0.26 | $0.13 (best) | — |
| Blended (3:1) | $2.15 | $2.92 | $0.925 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Alibaba API | Median of 39 providers |
| Limits | |||
| Context window | 200,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 65,536 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-5.1 | qwen3.6-max-preview | — |
| API providers | 40 | 10 | 41 (best) |
| Released | Apr 7, 2026 | Apr 20, 2026 | Aug 14, 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
- Qwen3.6 Max Preview$28.60
- Qwen3.8 27B$9.00
Which should you choose?
Which is better: GLM-5.1, Qwen3.6 Max Preview or Qwen3.8 27B?
Qwen3.8 27B is the better all-round choice, scoring 67/100 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, Qwen3.6 Max Preview or Qwen3.8 27B?
Qwen3.8 27B is cheaper at $0.40 input / $2.50 output per million tokens (median across 39 API providers). 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 $0.925 per million tokens for Qwen3.8 27B versus $2.15 for GLM-5.1 (2.3× as much) and $2.92 for Qwen3.6 Max Preview (3.2× 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), Qwen3.8 27B 149.4 (#53 of 148) and Qwen3.6 Max Preview 149.2 (#54 of 148). The confidence ranges of the top two overlap (148.0–151.6 vs 147.5–151.6), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.8 27B 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?
Qwen3.6 Max Preview and Qwen3.8 27B 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, Qwen3.6 Max Preview up to 65,536, Qwen3.8 27B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; Qwen3.6 Max Preview accepts text; Qwen3.8 27B accepts text, images and video. Qwen3.8 27B handles the widest range of inputs.
Are any of these open source?
GLM-5.1 and Qwen3.8 27B publishes its weights and can be self-hosted; Qwen3.6 Max Preview is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Qwen3.6 Max Preview came out Apr 20, 2026; GLM-5.1 came out Apr 7, 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.
