Qwen3.6 Max Preview vs Gemini 2.5 Pro vs GLM-5.1
Gemini 2.5 Pro comes out ahead, 63 to 57 and 54 on our weighted score, though GLM-5.1 is 37% cheaper per token.
Alibaba (Qwen)Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
- Our pick
GoogleGemini 2.5 Pro
63/100- ECI145.3
- Price$1.25 / $10.00
- Context1.05M
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
Gemini 2.5 Pro is our pick
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against GLM-5.1 (57) and Qwen3.6 Max Preview (54). It leads on inputs & features and context window. GLM-5.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · Qwen3.6 Max Preview 149.2 · Gemini 2.5 Pro 145.3
- Lowest priceGLM-5.1GLM-5.1 $2.15 · Qwen3.6 Max Preview $2.92 · Gemini 2.5 Pro $3.44 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · Qwen3.6 Max Preview 262,144 · GLM-5.1 200,000 tokens
- Widest inputsGemini 2.5 ProQwen3.6 Max Preview: Text · Gemini 2.5 Pro: Text, Images, PDFs, Audio, Video · GLM-5.1: Text
- Self-hostingGLM-5.1Publishes downloadable weights
| Measure | Weight | Qwen3.6 Max Preview | Gemini 2.5 Pro | GLM-5.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 77 | 72 | 78 |
| Price | 25% | 28 | 24 | 34 |
| Inputs & features | 15% | 35 | 100 | 45 |
| Context window | 10% | 37 | 61 | 32 |
| Overall | 100% | 54/100 | 63/100 | 57/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.6 Max PreviewAlibaba (Qwen) | Gemini 2.5 ProGoogle | GLM-5.1Z.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.2 | 145.3 | 149.9 (best) |
| ECI rank | #54 of 148 | #78 of 148 | #51 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 87.4% | 85.3% | 89.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 24.6% | 36.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 91.1% | 84.7% | 93.3% (best) |
| SWE-bench VerifiedFixing real GitHub issues | 76.7% (best) | 57.6% | 74.2% |
| SimpleQA VerifiedShort factual questions | 52.0% (best) | — | 34.0% |
| Price per million tokens | |||
| Input | $1.30 | $1.25 (best) | $1.40 |
| Output | $7.80 | $10.00 | $4.40 (best) |
| Cached input | $0.13 | $0.125 (best) | $0.26 |
| Blended (3:1) | $2.92 | $3.44 | $2.15 (best) |
| Long-context rate | Same rate | Over 200K: $2.50 / $15.00 | Same rate |
| Price source | Official Alibaba API | Official Google API | Official Z.AI API |
| Limits | |||
| Context window | 262,144 tokens | 1,048,576 tokens (best) | 200,000 tokens |
| Max output | 65,536 tokens | 65,536 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | qwen3.6-max-preview | gemini-2.5-pro | glm-5.1 |
| API providers | 10 | 22 | 40 (best) |
| Released | Apr 20, 2026 | Jun 17, 2025 | Apr 7, 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 Max Preview$28.60
- Gemini 2.5 Pro$32.50
- GLM-5.1$22.80
Which should you choose?
Which is better: Qwen3.6 Max Preview, Gemini 2.5 Pro or GLM-5.1?
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against GLM-5.1 (57) and Qwen3.6 Max Preview (54). It leads on inputs & features and context window. GLM-5.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3.6 Max Preview, Gemini 2.5 Pro or GLM-5.1?
GLM-5.1 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). Qwen3.6 Max Preview costs $1.30 input / $7.80 output per million tokens (official Alibaba API price); Gemini 2.5 Pro costs $1.25 input / $10.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $2.15 per million tokens for GLM-5.1 versus $2.92 for Qwen3.6 Max Preview (1.4× as much) and $3.44 for Gemini 2.5 Pro (1.6× 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), Qwen3.6 Max Preview 149.2 (#54 of 148) and Gemini 2.5 Pro 145.3 (#78 of 148). The confidence ranges of the top two overlap (148.0–151.6 vs 147.6–152.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, Qwen3.6 Max Preview 87.4%, Gemini 2.5 Pro 85.3%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, Qwen3.6 Max Preview 91.1%, Gemini 2.5 Pro 84.7%; SWE-bench Verified — Qwen3.6 Max Preview 76.7%, GLM-5.1 74.2%, Gemini 2.5 Pro 57.6%.
Which is better for coding?
Qwen3.6 Max Preview resolves more real GitHub issues on SWE-bench Verified: Qwen3.6 Max Preview 76.7%, GLM-5.1 74.2% and Gemini 2.5 Pro 57.6%. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.5 Pro has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.6 Max Preview and 200,000 for GLM-5.1. Maximum output per response: Qwen3.6 Max Preview up to 65,536, Gemini 2.5 Pro up to 65,536, GLM-5.1 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3.6 Max Preview accepts text; Gemini 2.5 Pro accepts text, images, PDFs, audio and video; GLM-5.1 accepts text. Gemini 2.5 Pro handles the widest range of inputs.
Are any of these open source?
GLM-5.1 publishes its weights and can be self-hosted; Qwen3.6 Max Preview and Gemini 2.5 Pro is proprietary.
Which is newer?
Qwen3.6 Max Preview is the newest, released Apr 20, 2026. GLM-5.1 came out Apr 7, 2026; Gemini 2.5 Pro came out Jun 17, 2025. Knowledge cutoff: Qwen3.6 Max Preview Apr 2025, Gemini 2.5 Pro 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.
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