GLM-4.7 vs Qwen3.5 35B-A3B vs Seed 2.0 Code
Qwen3.5 35B-A3B comes out ahead, 63 to 57 and 42 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-4.7
42/100- ECI143.5
- Price$0.60 / $2.20
- Context205K
- Our pick
Alibaba (Qwen)Qwen3.5 35B-A3B
63/100- ECI142.5
- Price$0.25 / $2.00
- Context262K
ByteDance SeedSeed 2.0 Code
57/100- ECI—
- Price$0.475 / $2.37
- Context262K
Qwen3.5 35B-A3B is our pick
Qwen3.5 35B-A3B is the better all-round choice, scoring 63/100 against Seed 2.0 Code (57) and GLM-4.7 (42). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3.5 35B-A3BQwen3.5 35B-A3B $0.688 · Seed 2.0 Code $0.95 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 35B-A3B and Seed 2.0 CodeQwen3.5 35B-A3B 262,144 · Seed 2.0 Code 262,144 · GLM-4.7 204,800 tokens
- Widest inputsQwen3.5 35B-A3BGLM-4.7: Text · Qwen3.5 35B-A3B: Text, Images, Audio, Video · Seed 2.0 Code: Text, Images, Video
- Self-hostingGLM-4.7 and Qwen3.5 35B-A3BPublishes downloadable weights
| Measure | Weight | GLM-4.7 | Qwen3.5 35B-A3B | Seed 2.0 Code |
|---|---|---|---|---|
| Price | 50% | 50 | 58 | 51 |
| Inputs & features | 30% | 35 | 90 | 80 |
| Context window | 20% | 32 | 37 | 37 |
| Overall | 100% | 42/100 | 63/100 | 57/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-4.7Z.ai (Zhipu) | Qwen3.5 35B-A3BAlibaba (Qwen) | Seed 2.0 CodeByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 143.5 (best) | 142.5 | — |
| ECI rank | #84 of 148 (best) | #88 of 148 | — |
| GPQA DiamondGraduate-level science questions | 83.3% | 83.5% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 83.3% (best) | 70.0% | — |
| SimpleQA VerifiedShort factual questions | 32.2% | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.25 (best) | $0.475 |
| Output | $2.20 | $2.00 (best) | $2.37 |
| Cached input | $0.11 | — | $0.095 (best) |
| Blended (3:1) | $1.00 | $0.688 (best) | $0.95 |
| Long-context rate | Same rate | Same rate | Over 32K: $0.712 / $3.56 |
| Price source | Official Z.AI API | Official Alibaba API | Official Volcengine Ark API |
| Limits | |||
| Context window | 204,800 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 65,536 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | Yes | Yes |
| Reasoning | Yes | Yes | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.7 | qwen3.5-35b-a3b | doubao-seed-2-0-code-preview-260215 |
| API providers | 20 (best) | 18 | 10 |
| Released | Dec 22, 2025 | Feb 23, 2026 | Feb 14, 2026 |
| 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-4.7$10.40
- Qwen3.5 35B-A3B$6.50
- Seed 2.0 Code$9.50
Which should you choose?
Which is better: GLM-4.7, Qwen3.5 35B-A3B or Seed 2.0 Code?
Qwen3.5 35B-A3B is the better all-round choice, scoring 63/100 against Seed 2.0 Code (57) and GLM-4.7 (42). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-4.7, Qwen3.5 35B-A3B or Seed 2.0 Code?
Qwen3.5 35B-A3B is cheaper at $0.25 input / $2.00 output per million tokens (official Alibaba API price). Seed 2.0 Code costs $0.475 input / $2.37 output per million tokens (official Volcengine Ark API price); GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.688 per million tokens for Qwen3.5 35B-A3B versus $0.95 for Seed 2.0 Code (1.4× as much) and $1.00 for GLM-4.7 (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.7 has an ECI of 143.5, Qwen3.5 35B-A3B has an ECI of 142.5 and Seed 2.0 Code has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7, Qwen3.5 35B-A3B and Seed 2.0 Code yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.5 35B-A3B and Seed 2.0 Code have the largest context windows (262,144 and 262,144 tokens), against 204,800 for GLM-4.7. Maximum output per response: GLM-4.7 up to 131,072, Qwen3.5 35B-A3B up to 65,536, Seed 2.0 Code up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7 accepts text; Qwen3.5 35B-A3B accepts text, images, audio and video; Seed 2.0 Code accepts text, images and video. Qwen3.5 35B-A3B handles the widest range of inputs.
Are any of these open source?
GLM-4.7 and Qwen3.5 35B-A3B publishes its weights and can be self-hosted; Seed 2.0 Code is proprietary.
Which is newer?
Qwen3.5 35B-A3B is the newest, released Feb 23, 2026. Seed 2.0 Code came out Feb 14, 2026; GLM-4.7 came out Dec 22, 2025. Knowledge cutoff: GLM-4.7 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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