GLM-5.2 vs Grok 4.7 vs Kimi K2.6
Too close to call on our weighted score (Grok 4.7 61, Kimi K2.6 60, GLM-5.2 55). The right pick depends on what you value most.
Too close to call
It is close. Our weighted score puts them within a point (Grok 4.7 61/100, Kimi K2.6 60/100, GLM-5.2 55/100), so choose by what matters most for your work: Grok 4.7 for raw capability, Kimi K2.6 on price and GLM-5.2 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because Grok 4.7 has no Capabilities Index score yet.
- CapabilityGrok 4.7Shared benchmarks: Grok 4.7 74.9% · Kimi K2.6 69.7% · GLM-5.2 67.9%
- Lowest priceKimi K2.6Kimi K2.6 $1.71 · GLM-5.2 $2.15 · Grok 4.7 $3.00 per 1M tokens (3:1 blend)
- Longest contextGLM-5.2GLM-5.2 1,000,000 · Grok 4.7 500,000 · Kimi K2.6 262,144 tokens
- Widest inputsGrok 4.7 and Kimi K2.6GLM-5.2: Text · Grok 4.7: Text, Images, PDFs · Kimi K2.6: Text, Images, Video
- Self-hostingGLM-5.2 and Kimi K2.6Publishes downloadable weights
| Measure | Weight | GLM-5.2 | Grok 4.7 | Kimi K2.6 |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 68 | 75 | 70 |
| Price | 25% | 34 | 27 | 39 |
| Inputs & features | 15% | 45 | 80 | 80 |
| Context window | 10% | 60 | 48 | 37 |
| Overall | 100% | 55/100 | 61/100 | 60/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification |  GLM-5.2Z.ai (Zhipu) |  Grok 4.7xAI |  Kimi K2.6Moonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 151.8 (best) | — | 151.1 |
| ECI rank | #44 of 148 (best) | — | #45 of 148 |
| GPQA DiamondGraduate-level science questions | 91.9% | 92.7% (best) | 90.8% |
| FrontierMath Tiers 1–3Research-level mathematics | 59.2% (best) | 53.0% | 57.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 86.4% | 98.1% (best) | 96.1% |
| SWE-bench VerifiedFixing real GitHub issues | 78.7% (best) | — | 76.7% |
| SimpleQA VerifiedShort factual questions | 34.2% | 56.0% (best) | 34.9% |
| Price per million tokens | |||
| Input | $1.40 | $2.00 | $0.95 (best) |
| Output | $4.40 | $6.00 | $4.00 (best) |
| Cached input | $0.26 | $0.50 | $0.16 (best) |
| Blended (3:1) | $2.15 | $3.00 | $1.71 (best) |
| Long-context rate | Same rate | Over 200K: $4.00 / $12.00 | Same rate |
| Price source | Official Z.AI API | Official xAI API | Official Moonshot AI API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 500,000 tokens | 262,144 tokens |
| Max output | 131,072 tokens | 500,000 tokens (best) | 262,144 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yeshigh · max | Yeslow · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-5.2 | grok-4.7 | kimi-k2.6 |
| API providers | 80 (best) | 17 | 46 |
| Released | Jun 13, 2026 | Sep 21, 2026 | Apr 21, 2026 |
| Knowledge cutoff | — | May 2026 | Jan 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-5.2$22.80
- Grok 4.7$32.00
- Kimi K2.6$17.50
Which should you choose?
Which is better: GLM-5.2, Grok 4.7 or Kimi K2.6?
It is close. Our weighted score puts them within a point (Grok 4.7 61/100, Kimi K2.6 60/100, GLM-5.2 55/100), so choose by what matters most for your work: Grok 4.7 for raw capability, Kimi K2.6 on price and GLM-5.2 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because Grok 4.7 has no Capabilities Index score yet.
Which is cheaper, GLM-5.2, Grok 4.7 or Kimi K2.6?
Kimi K2.6 is cheaper at $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). GLM-5.2 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price); Grok 4.7 costs $2.00 input / $6.00 output per million tokens (official xAI API price). At a typical mix of three input tokens to one output token, that is $1.71 per million tokens for Kimi K2.6 versus $2.15 for GLM-5.2 (1.3× as much) and $3.00 for Grok 4.7 (1.8× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified): Grok 4.7 74.9%, Kimi K2.6 69.7% and GLM-5.2 67.9%. On individual benchmarks: GPQA Diamond — Grok 4.7 92.7%, GLM-5.2 91.9%, Kimi K2.6 90.8%; FrontierMath Tiers 1–3 — GLM-5.2 59.2%, Kimi K2.6 57.2%, Grok 4.7 53.0%; OTIS Mock AIME 2024–2025 — Grok 4.7 98.1%, Kimi K2.6 96.1%, GLM-5.2 86.4%; SimpleQA Verified — Grok 4.7 56.0%, Kimi K2.6 34.9%, GLM-5.2 34.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Grok 4.7 yet, so there is no like-for-like coding score. On overall capability, Grok 4.7 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?
GLM-5.2 has the largest context window at 1,000,000 tokens, against 500,000 for Grok 4.7 and 262,144 for Kimi K2.6. Maximum output per response: GLM-5.2 up to 131,072, Grok 4.7 up to 500,000, Kimi K2.6 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-5.2 accepts text; Grok 4.7 accepts text, images and PDFs; Kimi K2.6 accepts text, images and video. Grok 4.7 handles the widest range of inputs.
Are any of these open source?
GLM-5.2 and Kimi K2.6 publishes its weights and can be self-hosted; Grok 4.7 is proprietary.
Which is newer?
Grok 4.7 is the newest, released Sep 21, 2026. GLM-5.2 came out Jun 13, 2026; Kimi K2.6 came out Apr 21, 2026. Knowledge cutoff: Grok 4.7 May 2026, Kimi K2.6 Jan 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.
