GLM-5.1 vs o3 vs Qwen3.6 Max Preview
Too close to call on our weighted score (o3 58, GLM-5.1 57, Qwen3.6 Max Preview 54). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
OpenAIo3
58/100- ECI146.9
- Price$2.00 / $8.00
- Context200K
Alibaba (Qwen)Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (o3 58/100, GLM-5.1 57/100, Qwen3.6 Max Preview 54/100), so choose by what matters most for your work: GLM-5.1 for raw capability and Qwen3.6 Max Preview for long inputs. 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 · o3 146.9
- Lowest priceGLM-5.1GLM-5.1 $2.15 · Qwen3.6 Max Preview $2.92 · o3 $3.50 per 1M tokens (3:1 blend)
- Longest contextQwen3.6 Max PreviewQwen3.6 Max Preview 262,144 · GLM-5.1 200,000 · o3 200,000 tokens
- Widest inputso3GLM-5.1: Text · o3: Text, Images, PDFs · Qwen3.6 Max Preview: Text
- Self-hostingGLM-5.1Publishes downloadable weights
| Measure | Weight | GLM-5.1 | o3 | Qwen3.6 Max Preview |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 74 | 77 |
| Price | 25% | 34 | 24 | 28 |
| Inputs & features | 15% | 45 | 80 | 35 |
| Context window | 10% | 32 | 32 | 37 |
| Overall | 100% | 57/100 | 58/100 | 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) | o3OpenAI | Qwen3.6 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.9 (best) | 146.9 | 149.2 |
| ECI rank | #51 of 148 (best) | #63 of 148 | #54 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | 81.8% | 87.4% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% (best) | 33.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% (best) | 84.4% | 91.1% |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% | 62.3% | 76.7% (best) |
| SimpleQA VerifiedShort factual questions | 34.0% | 49.4% | 52.0% (best) |
| Price per million tokens | |||
| Input | $1.40 | $2.00 | $1.30 (best) |
| Output | $4.40 (best) | $8.00 | $7.80 |
| Cached input | $0.26 | $0.50 | $0.13 (best) |
| Blended (3:1) | $2.15 (best) | $3.50 | $2.92 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 200,000 tokens | 200,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 100,000 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-5.1 | o3 | qwen3.6-max-preview |
| API providers | 40 (best) | 18 | 10 |
| Released | Apr 7, 2026 | Apr 16, 2025 | Apr 20, 2026 |
| Knowledge cutoff | — | May 2024 | 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
- o3$36.00
- Qwen3.6 Max Preview$28.60
Which should you choose?
Which is better: GLM-5.1, o3 or Qwen3.6 Max Preview?
It is close. Our weighted score puts them within a point (o3 58/100, GLM-5.1 57/100, Qwen3.6 Max Preview 54/100), so choose by what matters most for your work: GLM-5.1 for raw capability and Qwen3.6 Max Preview for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1, o3 or Qwen3.6 Max Preview?
GLM-5.1 is cheaper at $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); o3 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $2.15 per million tokens for GLM-5.1 versus $2.92 for Qwen3.6 Max Preview (1.4× as much) and $3.50 for o3 (1.6× 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 o3 146.9 (#63 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%, o3 81.8%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, Qwen3.6 Max Preview 91.1%, o3 84.4%; SWE-bench Verified — Qwen3.6 Max Preview 76.7%, GLM-5.1 74.2%, o3 62.3%; SimpleQA Verified — Qwen3.6 Max Preview 52.0%, o3 49.4%, GLM-5.1 34.0%.
Which is better for coding?
Qwen3.6 Max Preview resolves more real GitHub issues on SWE-bench Verified: Qwen3.6 Max Preview 76.7%, GLM-5.1 74.2% and o3 62.3%. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.6 Max Preview has the largest context window at 262,144 tokens, against 200,000 for GLM-5.1 and 200,000 for o3. Maximum output per response: GLM-5.1 up to 131,072, o3 up to 100,000, Qwen3.6 Max Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; o3 accepts text, images and PDFs; Qwen3.6 Max Preview accepts text. o3 handles the widest range of inputs.
Are any of these open source?
GLM-5.1 publishes its weights and can be self-hosted; o3 and 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; o3 came out Apr 16, 2025. Knowledge cutoff: o3 May 2024, 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.
