GLM-5.1 vs Kimi K2.7 Code vs Claude Sonnet 4.5
Kimi K2.7 Code comes out ahead, 64 to 57 and 55 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
- Our pick
Moonshot AIKimi K2.7 Code
64/100- ECI150.0
- Price$0.95 / $4.00
- Context262K
AnthropicClaude Sonnet 4.5
55/100- ECI146.8
- Price$3.00 / $15.00
- Context200K
Kimi K2.7 Code is our pick
Kimi K2.7 Code is the better all-round choice, scoring 64/100 against GLM-5.1 (57) and Claude Sonnet 4.5 (55). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K2.7 CodeCapabilities Index (ECI): Kimi K2.7 Code 150.0 · GLM-5.1 149.9 · Claude Sonnet 4.5 146.8
- Lowest priceKimi K2.7 CodeKimi K2.7 Code $1.71 · GLM-5.1 $2.15 · Claude Sonnet 4.5 $6.00 per 1M tokens (3:1 blend)
- Longest contextKimi K2.7 CodeKimi K2.7 Code 262,144 · GLM-5.1 200,000 · Claude Sonnet 4.5 200,000 tokens
- Widest inputsKimi K2.7 Code and Claude Sonnet 4.5GLM-5.1: Text · Kimi K2.7 Code: Text, Images, Video · Claude Sonnet 4.5: Text, Images, PDFs
- Self-hostingGLM-5.1 and Kimi K2.7 CodePublishes downloadable weights
| Measure | Weight | GLM-5.1 | Kimi K2.7 Code | Claude Sonnet 4.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 78 | 74 |
| Price | 25% | 34 | 39 | 13 |
| Inputs & features | 15% | 45 | 80 | 80 |
| Context window | 10% | 32 | 37 | 32 |
| Overall | 100% | 57/100 | 64/100 | 55/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.1Z.ai (Zhipu) | Kimi K2.7 CodeMoonshot AI | Claude Sonnet 4.5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.9 | 150.0 (best) | 146.8 |
| ECI rank | #51 of 148 | #49 of 148 (best) | #64 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | 87.9% | 82.3% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% | 54.0% (best) | 23.9% |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% | 95.6% (best) | 77.8% |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% (best) | — | 71.3% |
| SimpleQA VerifiedShort factual questions | 34.0% | 36.5% (best) | 30.7% |
| Price per million tokens | |||
| Input | $1.40 | $0.95 (best) | $3.00 |
| Output | $4.40 | $4.00 (best) | $15.00 |
| Cached input | $0.26 | $0.19 (best) | $0.30 |
| Blended (3:1) | $2.15 | $1.71 (best) | $6.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Moonshot AI API | Official Anthropic API |
| Limits | |||
| Context window | 200,000 tokens | 262,144 tokens (best) | 200,000 tokens |
| Max output | 131,072 tokens | 262,144 tokens (best) | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-5.1 | kimi-k2.7-code | claude-sonnet-4-5 |
| API providers | 40 | 51 (best) | 28 |
| Released | Apr 7, 2026 | Jun 12, 2026 | Sep 29, 2025 |
| Knowledge cutoff | — | Jan 2025 | Jul 31, 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
- Kimi K2.7 Code$17.50
- Claude Sonnet 4.5$60.00
Which should you choose?
Which is better: GLM-5.1, Kimi K2.7 Code or Claude Sonnet 4.5?
Kimi K2.7 Code is the better all-round choice, scoring 64/100 against GLM-5.1 (57) and Claude Sonnet 4.5 (55). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1, Kimi K2.7 Code or Claude Sonnet 4.5?
Kimi K2.7 Code is cheaper at $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price); Claude Sonnet 4.5 costs $3.00 input / $15.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $1.71 per million tokens for Kimi K2.7 Code versus $2.15 for GLM-5.1 (1.3× as much) and $6.00 for Claude Sonnet 4.5 (3.5× as much).
Which scores higher on benchmarks?
Kimi K2.7 Code scores higher on the Capabilities Index (ECI): Kimi K2.7 Code 150.0 (#49 of 148), GLM-5.1 149.9 (#51 of 148) and Claude Sonnet 4.5 146.8 (#64 of 148). The confidence ranges of the top two overlap (148.1–151.8 vs 148.0–151.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, Kimi K2.7 Code 87.9%, Claude Sonnet 4.5 82.3%; FrontierMath Tiers 1–3 — Kimi K2.7 Code 54.0%, GLM-5.1 36.8%, Claude Sonnet 4.5 23.9%; OTIS Mock AIME 2024–2025 — Kimi K2.7 Code 95.6%, GLM-5.1 93.3%, Claude Sonnet 4.5 77.8%; SimpleQA Verified — Kimi K2.7 Code 36.5%, GLM-5.1 34.0%, Claude Sonnet 4.5 30.7%.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K2.7 Code yet, so there is no like-for-like coding score. On overall capability, Kimi K2.7 Code leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Kimi K2.7 Code has the largest context window at 262,144 tokens, against 200,000 for GLM-5.1 and 200,000 for Claude Sonnet 4.5. Maximum output per response: GLM-5.1 up to 131,072, Kimi K2.7 Code up to 262,144, Claude Sonnet 4.5 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; Kimi K2.7 Code accepts text, images and video; Claude Sonnet 4.5 accepts text, images and PDFs. Kimi K2.7 Code handles the widest range of inputs.
Are any of these open source?
GLM-5.1 and Kimi K2.7 Code publishes its weights and can be self-hosted; Claude Sonnet 4.5 is proprietary.
Which is newer?
Kimi K2.7 Code is the newest, released Jun 12, 2026. GLM-5.1 came out Apr 7, 2026; Claude Sonnet 4.5 came out Sep 29, 2025. Knowledge cutoff: Kimi K2.7 Code Jan 2025, Claude Sonnet 4.5 Jul 31, 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.
