GLM-5.3 vs GLM-5.2
Too close to call on our weighted score (GLM-5.3 64, GLM-5.2 61). The right pick depends on what you value most.
Too close to call
It is close. Our weighted score puts them within 3 points (GLM-5.3 64/100, GLM-5.2 61/100), so choose by what matters most for your work: GLM-5.3 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.3Capabilities Index (ECI): GLM-5.3 155.8 · GLM-5.2 151.8
- Lowest priceSame priceGLM-5.3 $2.15 · GLM-5.2 $2.15 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGLM-5.3 1,000,000 · GLM-5.2 1,000,000 tokens
- Widest inputsSame inputsGLM-5.3: Text · GLM-5.2: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5.3 | GLM-5.2 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 85 | 80 |
| Price | 25% | 34 | 34 |
| Inputs & features | 15% | 45 | 45 |
| Context window | 10% | 60 | 60 |
| Overall | 100% | 64/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification |  GLM-5.3Z.ai (Zhipu) | GLM-5.2Z.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 155.8 (best) | 151.8 |
| ECI rank | #24 of 148 (best) | #44 of 148 |
| GPQA DiamondGraduate-level science questions | 90.9% | 91.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 68.8% (best) | 59.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% (best) | 86.4% |
| SWE-bench VerifiedFixing real GitHub issues | — | 78.7% |
| SimpleQA VerifiedShort factual questions | 41.0% (best) | 34.2% |
| Price per million tokens | ||
| Input | $1.40 | $1.40 |
| Output | $4.40 | $4.40 |
| Cached input | $0.26 | $0.26 |
| Blended (3:1) | $2.15 | $2.15 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Z.AI API |
| Limits | ||
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · high · max | Yeshigh · max |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Open | Open |
| API model ID | glm-5.3 | glm-5.2 |
| API providers | 62 | 80 (best) |
| Released | Aug 14, 2026 | Jun 13, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5.3$22.80
- GLM-5.2$22.80
Which should you choose?
Which is better: GLM-5.3 or GLM-5.2?
It is close. Our weighted score puts them within 3 points (GLM-5.3 64/100, GLM-5.2 61/100), so choose by what matters most for your work: GLM-5.3 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.3 or GLM-5.2?
GLM-5.3 and GLM-5.2 cost the same: $1.40 input / $4.40 output per million tokens.
Which scores higher on benchmarks?
GLM-5.3 scores higher on the Capabilities Index (ECI): GLM-5.3 155.8 (#24 of 148) and GLM-5.2 151.8 (#44 of 148). The confidence ranges of the top two overlap (153.7–158.3 vs 149.8–154.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.2 91.9%, GLM-5.3 90.9%; FrontierMath Tiers 1–3 — GLM-5.3 68.8%, GLM-5.2 59.2%; OTIS Mock AIME 2024–2025 — GLM-5.3 91.1%, GLM-5.2 86.4%; SimpleQA Verified — GLM-5.3 41.0%, GLM-5.2 34.2%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3 yet, so there is no like-for-like coding score. On overall capability, GLM-5.3 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
GLM-5.3 and GLM-5.2 share the same 1,000,000-token context window. Maximum output per response: GLM-5.3 up to 131,072, GLM-5.2 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3 accepts text; GLM-5.2 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
GLM-5.3 is the newest, released Aug 14, 2026. GLM-5.2 came out Jun 13, 2026.
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.
