GLM-5.1 vs GPT-5.2 vs Claude Sonnet 4.6
Too close to call on our weighted score (Claude Sonnet 4.6 62, GPT-5.2 61, GLM-5.1 57). 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
OpenAIGPT-5.2
61/100- ECI153.5
- Price$1.75 / $14.00
- Context400K
AnthropicClaude Sonnet 4.6
62/100- ECI152.3
- Price$3.00 / $15.00
- Context1M
Too close to call
It is close. Our weighted score puts them within 1 points (Claude Sonnet 4.6 62/100, GPT-5.2 61/100, GLM-5.1 57/100), so choose by what matters most for your work: GPT-5.2 for raw capability, GLM-5.1 on price and Claude Sonnet 4.6 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.2Capabilities Index (ECI): GPT-5.2 153.5 · Claude Sonnet 4.6 152.3 · GLM-5.1 149.9
- Lowest priceGLM-5.1GLM-5.1 $2.15 · GPT-5.2 $4.81 · Claude Sonnet 4.6 $6.00 per 1M tokens (3:1 blend)
- Longest contextClaude Sonnet 4.6Claude Sonnet 4.6 1,000,000 · GPT-5.2 400,000 · GLM-5.1 200,000 tokens
- Widest inputsClaude Sonnet 4.6GLM-5.1: Text · GPT-5.2: Text, Images · Claude Sonnet 4.6: Text, Images, PDFs
- Self-hostingGLM-5.1Publishes downloadable weights
| Measure | Weight | GLM-5.1 | GPT-5.2 | Claude Sonnet 4.6 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 83 | 81 |
| Price | 25% | 34 | 18 | 13 |
| Inputs & features | 15% | 45 | 70 | 80 |
| Context window | 10% | 32 | 44 | 60 |
| Overall | 100% | 57/100 | 61/100 | 62/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.1Z.ai (Zhipu) | GPT-5.2OpenAI | Claude Sonnet 4.6Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.9 | 153.5 (best) | 152.3 |
| ECI rank | #51 of 148 | #38 of 148 (best) | #40 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% | 91.4% (best) | 87.4% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% | 67.4% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% | 96.1% (best) | 85.8% |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% | 73.8% | 75.2% (best) |
| SimpleQA VerifiedShort factual questions | 34.0% | 37.1% (best) | 35.5% |
| Price per million tokens | |||
| Input | $1.40 (best) | $1.75 | $3.00 |
| Output | $4.40 (best) | $14.00 | $15.00 |
| Cached input | $0.26 | $0.175 (best) | $0.30 |
| Blended (3:1) | $2.15 (best) | $4.81 | $6.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official OpenAI API | Official Anthropic API |
| Limits | |||
| Context window | 200,000 tokens | 400,000 tokens | 1,000,000 tokens (best) |
| Max output | 131,072 tokens (best) | 128,000 tokens | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh | Yeslow · medium · high · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-5.1 | gpt-5.2 | claude-sonnet-4-6 |
| API providers | 40 | 21 | 41 (best) |
| Released | Apr 7, 2026 | Dec 11, 2025 | Feb 17, 2026 |
| Knowledge cutoff | — | Aug 31, 2025 | Aug 31, 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
- GPT-5.2$45.50
- Claude Sonnet 4.6$60.00
Which should you choose?
Which is better: GLM-5.1, GPT-5.2 or Claude Sonnet 4.6?
It is close. Our weighted score puts them within 1 points (Claude Sonnet 4.6 62/100, GPT-5.2 61/100, GLM-5.1 57/100), so choose by what matters most for your work: GPT-5.2 for raw capability, GLM-5.1 on price and Claude Sonnet 4.6 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1, GPT-5.2 or Claude Sonnet 4.6?
GLM-5.1 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). GPT-5.2 costs $1.75 input / $14.00 output per million tokens (official OpenAI API price); Claude Sonnet 4.6 costs $3.00 input / $15.00 output per million tokens (official Anthropic 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 $4.81 for GPT-5.2 (2.2× as much) and $6.00 for Claude Sonnet 4.6 (2.8× as much).
Which scores higher on benchmarks?
GPT-5.2 scores higher on the Capabilities Index (ECI): GPT-5.2 153.5 (#38 of 148), Claude Sonnet 4.6 152.3 (#40 of 148) and GLM-5.1 149.9 (#51 of 148). The confidence ranges of the top two overlap (151.7–155.4 vs 149.6–154.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-5.2 91.4%, GLM-5.1 89.9%, Claude Sonnet 4.6 87.4%; OTIS Mock AIME 2024–2025 — GPT-5.2 96.1%, GLM-5.1 93.3%, Claude Sonnet 4.6 85.8%; SWE-bench Verified — Claude Sonnet 4.6 75.2%, GLM-5.1 74.2%, GPT-5.2 73.8%; SimpleQA Verified — GPT-5.2 37.1%, Claude Sonnet 4.6 35.5%, GLM-5.1 34.0%.
Which is better for coding?
Claude Sonnet 4.6 resolves more real GitHub issues on SWE-bench Verified: Claude Sonnet 4.6 75.2%, GLM-5.1 74.2% and GPT-5.2 73.8%. All three support tool calling for agent workflows.
Which has the bigger context window?
Claude Sonnet 4.6 has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5.2 and 200,000 for GLM-5.1. Maximum output per response: GLM-5.1 up to 131,072, GPT-5.2 up to 128,000, Claude Sonnet 4.6 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; GPT-5.2 accepts text and images; Claude Sonnet 4.6 accepts text, images and PDFs. Claude Sonnet 4.6 handles the widest range of inputs.
Are any of these open source?
GLM-5.1 publishes its weights and can be self-hosted; GPT-5.2 and Claude Sonnet 4.6 is proprietary.
Which is newer?
GLM-5.1 is the newest, released Apr 7, 2026. Claude Sonnet 4.6 came out Feb 17, 2026; GPT-5.2 came out Dec 11, 2025. Knowledge cutoff: GPT-5.2 Aug 31, 2025, Claude Sonnet 4.6 Aug 31, 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.
