GLM-5.1 vs Qwen3 235B-A22B
GLM-5.1 comes out ahead, 57 to 51 on our weighted score, though Qwen3 235B-A22B is 43% cheaper per token.
- Our pick
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
Alibaba (Qwen)Qwen3 235B-A22B
51/100- ECI139.4
- Price$0.70 / $2.80
- Context131K
Add a model
Make it a three-way comparison.
GLM-5.1 is our pick
GLM-5.1 is the better all-round choice, scoring 57/100 against Qwen3 235B-A22B (51). It leads on capability, inputs & features and context window. Qwen3 235B-A22B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · Qwen3 235B-A22B 139.4
- Lowest priceQwen3 235B-A22BQwen3 235B-A22B $1.23 · GLM-5.1 $2.15 per 1M tokens (3:1 blend)
- Longest contextGLM-5.1GLM-5.1 200,000 · Qwen3 235B-A22B 131,072 tokens
- Widest inputsSame inputsGLM-5.1: Text · Qwen3 235B-A22B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5.1 | Qwen3 235B-A22B |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 65 |
| Price | 25% | 34 | 46 |
| Inputs & features | 15% | 45 | 35 |
| Context window | 10% | 32 | 24 |
| Overall | 100% | 57/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.1Z.ai (Zhipu) | Qwen3 235B-A22BAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 149.9 (best) | 139.4 |
| ECI rank | #51 of 148 (best) | #103 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | 70.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% | — |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% | — |
| SimpleQA VerifiedShort factual questions | 34.0% | — |
| Price per million tokens | ||
| Input | $1.40 | $0.70 (best) |
| Output | $4.40 | $2.80 (best) |
| Cached input | $0.26 | — |
| Blended (3:1) | $2.15 | $1.23 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Alibaba API |
| Limits | ||
| Context window | 200,000 tokens (best) | 131,072 tokens |
| Max output | 131,072 tokens (best) | 16,384 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | glm-5.1 | qwen3-235b-a22b |
| API providers | 40 (best) | 7 |
| Released | Apr 7, 2026 | Apr 28, 2025 |
| 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 235B-A22B$12.60
Which should you choose?
Which is better: GLM-5.1 or Qwen3 235B-A22B?
GLM-5.1 is the better all-round choice, scoring 57/100 against Qwen3 235B-A22B (51). It leads on capability, inputs & features and context window. Qwen3 235B-A22B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1 or Qwen3 235B-A22B?
Qwen3 235B-A22B is cheaper at $0.70 input / $2.80 output per million tokens (official Alibaba API price). GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.23 per million tokens for Qwen3 235B-A22B versus $2.15 for GLM-5.1 (1.8× 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 Qwen3 235B-A22B 139.4 (#103 of 148). Their confidence ranges do not overlap (148.0–151.6 vs 135.2–140.8), so the gap is a real one. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, Qwen3 235B-A22B 70.7%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B 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. Both support tool calling for agent workflows.
Which has the bigger context window?
GLM-5.1 has the largest context window at 200,000 tokens, against 131,072 for Qwen3 235B-A22B. Maximum output per response: GLM-5.1 up to 131,072, Qwen3 235B-A22B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; Qwen3 235B-A22B 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-5.1 is the newest, released Apr 7, 2026. Qwen3 235B-A22B came out Apr 28, 2025. Knowledge cutoff: Qwen3 235B-A22B 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.
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