o3 vs GLM-5.1
Too close to call on our weighted score (o3 58, GLM-5.1 57). The right pick depends on what you value most.
Too close to call
It is close. Our weighted score puts them within a point (o3 58/100, GLM-5.1 57/100), so choose by what matters most for your work: GLM-5.1 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · o3 146.9
- Lowest priceGLM-5.1GLM-5.1 $2.15 · o3 $3.50 per 1M tokens (3:1 blend)
- Longest contextAbout the sameo3 200,000 · GLM-5.1 200,000 tokens
- Widest inputso3o3: Text, Images, PDFs · GLM-5.1: Text
- Self-hostingGLM-5.1Publishes downloadable weights
| Measure | Weight | o3 | GLM-5.1 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 74 | 78 |
| Price | 25% | 24 | 34 |
| Inputs & features | 15% | 80 | 45 |
| Context window | 10% | 32 | 32 |
| Overall | 100% | 58/100 | 57/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification |  o3OpenAI |  GLM-5.1Z.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 146.9 | 149.9 (best) |
| ECI rank | #63 of 148 | #51 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 81.8% | 89.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 33.3% | 36.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 84.4% | 93.3% (best) |
| SWE-bench VerifiedFixing real GitHub issues | 62.3% | 74.2% (best) |
| SimpleQA VerifiedShort factual questions | 49.4% (best) | 34.0% |
| Price per million tokens | ||
| Input | $2.00 | $1.40 (best) |
| Output | $8.00 | $4.40 (best) |
| Cached input | $0.50 | $0.26 (best) |
| Blended (3:1) | $3.50 | $2.15 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Z.AI API |
| Limits | ||
| Context window | 200,000 tokens | 200,000 tokens |
| Max output | 100,000 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | o3 | glm-5.1 |
| API providers | 18 | 40 (best) |
| Released | Apr 16, 2025 | Apr 7, 2026 |
| Knowledge cutoff | May 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o3$36.00
- GLM-5.1$22.80
Which should you choose?
Which is better: o3 or GLM-5.1?
It is close. Our weighted score puts them within a point (o3 58/100, GLM-5.1 57/100), so choose by what matters most for your work: GLM-5.1 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, o3 or GLM-5.1?
GLM-5.1 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI 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 $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) and o3 146.9 (#63 of 148). The confidence ranges of the top two overlap (148.0–151.6 vs 144.9–148.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, o3 81.8%; FrontierMath Tiers 1–3 — GLM-5.1 36.8%, o3 33.3%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, o3 84.4%; SWE-bench Verified — GLM-5.1 74.2%, o3 62.3%; SimpleQA Verified — o3 49.4%, GLM-5.1 34.0%.
Which is better for coding?
GLM-5.1 resolves more real GitHub issues on SWE-bench Verified: GLM-5.1 74.2% and o3 62.3%. Both support tool calling for agent workflows.
Which has the bigger context window?
o3 and GLM-5.1 share the same 200,000-token context window. Maximum output per response: o3 up to 100,000, GLM-5.1 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
o3 accepts text, images and PDFs; GLM-5.1 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 is proprietary.
Which is newer?
GLM-5.1 is the newest, released Apr 7, 2026. o3 came out Apr 16, 2025. Knowledge cutoff: o3 May 2024.
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.
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