GLM-4.7 vs Kimi K2 Thinking vs Seed 2.0 Code
Seed 2.0 Code comes out ahead, 57 to 42 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
Moonshot AIKimi K2 Thinking
42/100- ECI146.0
- Price$0.60 / $2.50
- Context262K
- Our pick
ByteDance SeedSeed 2.0 Code
57/100- ECI—
- Price$0.475 / $2.37
- Context262K
Seed 2.0 Code is our pick
Seed 2.0 Code is the better all-round choice, scoring 57/100 against Kimi K2 Thinking (42) and GLM-4.7 (42). It leads on 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 2.0 CodeSeed 2.0 Code $0.95 · GLM-4.7 $1.00 · Kimi K2 Thinking $1.07 per 1M tokens (3:1 blend)
- Longest contextKimi K2 Thinking and Seed 2.0 CodeKimi K2 Thinking 262,144 · Seed 2.0 Code 262,144 · GLM-4.7 204,800 tokens
- Widest inputsSeed 2.0 CodeGLM-4.7: Text · Kimi K2 Thinking: Text · Seed 2.0 Code: Text, Images, Video
- Self-hostingGLM-4.7 and Kimi K2 ThinkingPublishes downloadable weights
| Measure | Weight | GLM-4.7 | Kimi K2 Thinking | Seed 2.0 Code |
|---|---|---|---|---|
| Price | 50% | 50 | 48 | 51 |
| Inputs & features | 30% | 35 | 35 | 80 |
| Context window | 20% | 32 | 37 | 37 |
| Overall | 100% | 42/100 | 42/100 | 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) | Kimi K2 ThinkingMoonshot AI | Seed 2.0 CodeByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 143.5 | 146.0 (best) | — |
| ECI rank | #84 of 148 | #72 of 148 (best) | — |
| GPQA DiamondGraduate-level science questions | 83.3% | 84.2% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 83.3% (best) | 83.1% | — |
| SimpleQA VerifiedShort factual questions | 32.2% | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.60 | $0.475 (best) |
| Output | $2.20 (best) | $2.50 | $2.37 |
| Cached input | $0.11 | — | $0.095 (best) |
| Blended (3:1) | $1.00 | $1.07 | $0.95 (best) |
| Long-context rate | Same rate | Same rate | Over 32K: $0.712 / $3.56 |
| Price source | Official Z.AI API | Median of 10 providers | Official Volcengine Ark API |
| Limits | |||
| Context window | 204,800 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 131,072 tokens | 262,144 tokens (best) | 131,072 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 | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.7 | — | doubao-seed-2-0-code-preview-260215 |
| API providers | 20 (best) | 10 | 10 |
| Released | Dec 22, 2025 | Nov 6, 2025 | Feb 14, 2026 |
| Knowledge cutoff | Apr 2025 | Aug 2024 | — |
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
- Kimi K2 Thinking$11.00
- Seed 2.0 Code$9.50
Which should you choose?
Which is better: GLM-4.7, Kimi K2 Thinking or Seed 2.0 Code?
Seed 2.0 Code is the better all-round choice, scoring 57/100 against Kimi K2 Thinking (42) and GLM-4.7 (42). It leads on 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, Kimi K2 Thinking or Seed 2.0 Code?
Seed 2.0 Code is cheaper at $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); Kimi K2 Thinking costs $0.60 input / $2.50 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.95 per million tokens for Seed 2.0 Code versus $1.00 for GLM-4.7 (1.1× as much) and $1.07 for Kimi K2 Thinking (1.1× 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, Kimi K2 Thinking has an ECI of 146.0 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, Kimi K2 Thinking 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?
Kimi K2 Thinking 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, Kimi K2 Thinking up to 262,144, Seed 2.0 Code up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7 accepts text; Kimi K2 Thinking accepts text; Seed 2.0 Code accepts text, images and video. Seed 2.0 Code handles the widest range of inputs.
Are any of these open source?
GLM-4.7 and Kimi K2 Thinking publishes its weights and can be self-hosted; Seed 2.0 Code is proprietary.
Which is newer?
Seed 2.0 Code is the newest, released Feb 14, 2026. GLM-4.7 came out Dec 22, 2025; Kimi K2 Thinking came out Nov 6, 2025. Knowledge cutoff: GLM-4.7 Apr 2025, Kimi K2 Thinking Aug 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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