GLM-4.7 vs Qwen3 235B-A22B Thinking 2507 vs Seed 1.6 Flash
Seed 1.6 Flash comes out ahead, 81 to 42 and 41 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-4.7
41/100- ECI143.7
- Price$0.60 / $2.20
- Context205K
Alibaba (Qwen)Qwen3 235B-A22B Thinking 2507
42/100- ECI143.8
- Price$0.30 / $2.90
- Context262K
- Our pick
ByteDance SeedSeed 1.6 Flash
81/100- ECI—
- Price$0.022 / $0.223
- Context256K
Seed 1.6 Flash is our pick
Seed 1.6 Flash is the better all-round choice, scoring 81/100 against Qwen3 235B-A22B Thinking 2507 (42) and GLM-4.7 (41). 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 priceSeed 1.6 FlashSeed 1.6 Flash $0.072 · Qwen3 235B-A22B Thinking 2507 $0.95 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Thinking 2507Qwen3 235B-A22B Thinking 2507 262,144 · Seed 1.6 Flash 256,000 · GLM-4.7 204,800 tokens
- Widest inputsSeed 1.6 FlashGLM-4.7: Text · Qwen3 235B-A22B Thinking 2507: Text · Seed 1.6 Flash: Text, Images, Video
- Self-hostingGLM-4.7 and Qwen3 235B-A22B Thinking 2507Publishes downloadable weights (Apache 2.0)
| Measure | Weight | GLM-4.7 | Qwen3 235B-A22B Thinking 2507 | Seed 1.6 Flash |
|---|---|---|---|---|
| Price | 50% | 48 | 49 | 100 |
| Inputs & features | 30% | 35 | 35 | 80 |
| Context window | 20% | 32 | 37 | 36 |
| Overall | 100% | 41/100 | 42/100 | 81/100 |
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 235B-A22B Thinking 2507Alibaba (Qwen) | Seed 1.6 FlashByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 143.7 | 143.8 (best) | — |
| ECI rank | #94 of 165 | #93 of 165 (best) | — |
| GPQA DiamondGraduate-level science questions | 83.3% (best) | 80.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 83.3% | 86.7% (best) | — |
| SimpleQA VerifiedShort factual questions | 32.2% | 40.4% (best) | — |
| Price per million tokens | |||
| Input | $0.60 | $0.30 | $0.022 (best) |
| Output | $2.20 | $2.90 | $0.223 (best) |
| Cached input | $0.11 | — | $0.0044 (best) |
| Blended (3:1) | $1.00 | $0.95 | $0.072 (best) |
| Long-context rate | Same rate | Same rate | Over 32K: $0.045 / $0.445 |
| Price source | Official Z.AI API | Median of 11 providers | Official Volcengine Ark API |
| Limits | |||
| Context window | 204,800 tokens | 262,144 tokens (best) | 256,000 tokens |
| Max output | 131,072 tokens (best) | 81,920 tokens | 32,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | glm-4.7 | — | doubao-seed-1-6-flash-250828 |
| API providers | 31 (best) | 12 | 5 |
| Released | Dec 22, 2025 | Jul 25, 2025 | Aug 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-4.7$10.40
- Qwen3 235B-A22B Thinking 2507$8.80
- Seed 1.6 Flash$0.668
Which should you choose?
Which is better: GLM-4.7, Qwen3 235B-A22B Thinking 2507 or Seed 1.6 Flash?
Seed 1.6 Flash is the better all-round choice, scoring 81/100 against Qwen3 235B-A22B Thinking 2507 (42) and GLM-4.7 (41). 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 235B-A22B Thinking 2507 or Seed 1.6 Flash?
Seed 1.6 Flash is cheaper at $0.022 input / $0.223 output per million tokens (official Volcengine Ark API price). Qwen3 235B-A22B Thinking 2507 costs $0.30 input / $2.90 output per million tokens (median across 11 API providers); 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 $0.072 per million tokens for Seed 1.6 Flash versus $0.95 for Qwen3 235B-A22B Thinking 2507 (13× as much) and $1.00 for GLM-4.7 (14× 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 143.7, Qwen3 235B-A22B Thinking 2507 has an ECI of 143.8 and Seed 1.6 Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7, Qwen3 235B-A22B Thinking 2507 and Seed 1.6 Flash 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 235B-A22B Thinking 2507 has the largest context window at 262,144 tokens, against 256,000 for Seed 1.6 Flash and 204,800 for GLM-4.7. Maximum output per response: GLM-4.7 up to 131,072, Qwen3 235B-A22B Thinking 2507 up to 81,920, Seed 1.6 Flash up to 32,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7 accepts text; Qwen3 235B-A22B Thinking 2507 accepts text; Seed 1.6 Flash accepts text, images and video. Seed 1.6 Flash handles the widest range of inputs.
Are any of these open source?
GLM-4.7 and Qwen3 235B-A22B Thinking 2507 publishes its weights (Apache 2.0) and can be self-hosted; Seed 1.6 Flash is proprietary.
Which is newer?
GLM-4.7 is the newest, released Dec 22, 2025. Seed 1.6 Flash came out Aug 28, 2025; Qwen3 235B-A22B Thinking 2507 came out Jul 25, 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 Nov 2, 2026.
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