Qwen3.6 Plus vs GLM-5.1 vs Kimi K2.5
Too close to call on our weighted score (Qwen3.6 Plus 66, Kimi K2.5 65, GLM-5.1 57). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3.6 Plus
66/100- ECI147.6
- Price$0.50 / $3.00
- Context1M
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
Moonshot AIKimi K2.5
65/100- ECI148.0
- Price$0.60 / $3.00
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Qwen3.6 Plus 66/100, Kimi K2.5 65/100, GLM-5.1 57/100), so choose by what matters most for your work: GLM-5.1 for raw capability, Qwen3.6 Plus on price and Qwen3.6 Plus for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · Kimi K2.5 148.0 · Qwen3.6 Plus 147.6
- Lowest priceQwen3.6 PlusQwen3.6 Plus $1.13 · Kimi K2.5 $1.20 · GLM-5.1 $2.15 per 1M tokens (3:1 blend)
- Longest contextQwen3.6 PlusQwen3.6 Plus 1,000,000 · Kimi K2.5 262,144 · GLM-5.1 200,000 tokens
- Widest inputsQwen3.6 Plus and Kimi K2.5Qwen3.6 Plus: Text, Images, Video · GLM-5.1: Text · Kimi K2.5: Text, Images, Video
- Self-hostingGLM-5.1 and Kimi K2.5Publishes downloadable weights
| Measure | Weight | Qwen3.6 Plus | GLM-5.1 | Kimi K2.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 75 | 78 | 76 |
| Price | 25% | 47 | 34 | 46 |
| Inputs & features | 15% | 70 | 45 | 80 |
| Context window | 10% | 60 | 32 | 37 |
| Overall | 100% | 66/100 | 57/100 | 65/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.6 PlusAlibaba (Qwen) | GLM-5.1Z.ai (Zhipu) | Kimi K2.5Moonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 147.6 | 149.9 (best) | 148.0 |
| ECI rank | #59 of 148 | #51 of 148 (best) | #58 of 148 |
| GPQA DiamondGraduate-level science questions | 88.4% | 89.9% (best) | 87.6% |
| FrontierMath Tiers 1–3Research-level mathematics | 38.3% (best) | 36.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% (best) | 93.3% (best) | 92.2% |
| SWE-bench VerifiedFixing real GitHub issues | 57.9% | 74.2% (best) | 73.8% |
| SimpleQA VerifiedShort factual questions | 44.1% (best) | 34.0% | 34.3% |
| Price per million tokens | |||
| Input | $0.50 (best) | $1.40 | $0.60 |
| Output | $3.00 (best) | $4.40 | $3.00 (best) |
| Cached input | $0.05 (best) | $0.26 | — |
| Blended (3:1) | $1.13 (best) | $2.15 | $1.20 |
| Long-context rate | Over 256K: $2.00 / $6.00 | Same rate | Same rate |
| Price source | Official Alibaba API | Official Z.AI API | Median of 21 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 200,000 tokens | 262,144 tokens |
| Max output | 65,536 tokens | 131,072 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | qwen3.6-plus | glm-5.1 | — |
| API providers | 18 | 40 (best) | 21 |
| Released | Apr 2, 2026 | Apr 7, 2026 | Jan 27, 2026 |
| Knowledge cutoff | Apr 2025 | — | 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.
- Qwen3.6 Plus$11.00
- GLM-5.1$22.80
- Kimi K2.5$12.00
Which should you choose?
Which is better: Qwen3.6 Plus, GLM-5.1 or Kimi K2.5?
It is close. Our weighted score puts them within a point (Qwen3.6 Plus 66/100, Kimi K2.5 65/100, GLM-5.1 57/100), so choose by what matters most for your work: GLM-5.1 for raw capability, Qwen3.6 Plus on price and Qwen3.6 Plus for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3.6 Plus, GLM-5.1 or Kimi K2.5?
Qwen3.6 Plus is cheaper at $0.50 input / $3.00 output per million tokens (official Alibaba API price). Kimi K2.5 costs $0.60 input / $3.00 output per million tokens (median across 21 API providers); GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.13 per million tokens for Qwen3.6 Plus versus $1.20 for Kimi K2.5 (1.1× as much) and $2.15 for GLM-5.1 (1.9× as much).
Which scores higher on benchmarks?
GLM-5.1 scores higher on the Capabilities Index (ECI): GLM-5.1 149.9 (#51 of 148), Kimi K2.5 148.0 (#58 of 148) and Qwen3.6 Plus 147.6 (#59 of 148). The confidence ranges of the top two overlap (148.0–151.6 vs 146.5–149.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, Qwen3.6 Plus 88.4%, Kimi K2.5 87.6%; OTIS Mock AIME 2024–2025 — Qwen3.6 Plus 93.3%, GLM-5.1 93.3%, Kimi K2.5 92.2%; SWE-bench Verified — GLM-5.1 74.2%, Kimi K2.5 73.8%, Qwen3.6 Plus 57.9%; SimpleQA Verified — Qwen3.6 Plus 44.1%, Kimi K2.5 34.3%, GLM-5.1 34.0%.
Which is better for coding?
GLM-5.1 resolves more real GitHub issues on SWE-bench Verified: GLM-5.1 74.2%, Kimi K2.5 73.8% and Qwen3.6 Plus 57.9%. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.6 Plus has the largest context window at 1,000,000 tokens, against 262,144 for Kimi K2.5 and 200,000 for GLM-5.1. Maximum output per response: Qwen3.6 Plus up to 65,536, GLM-5.1 up to 131,072, Kimi K2.5 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Qwen3.6 Plus accepts text, images and video; GLM-5.1 accepts text; Kimi K2.5 accepts text, images and video. Qwen3.6 Plus handles the widest range of inputs.
Are any of these open source?
GLM-5.1 and Kimi K2.5 publishes its weights and can be self-hosted; Qwen3.6 Plus is proprietary.
Which is newer?
GLM-5.1 is the newest, released Apr 7, 2026. Qwen3.6 Plus came out Apr 2, 2026; Kimi K2.5 came out Jan 27, 2026. Knowledge cutoff: Qwen3.6 Plus Apr 2025, Kimi K2.5 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.
