Gemini 3.1 Pro Preview vs Qwen3.6 Max Preview
Gemini 3.1 Pro Preview comes out ahead, 68 to 54 on our weighted score, though Qwen3.6 Max Preview is 35% cheaper per token.
- Our pick
GoogleGemini 3.1 Pro Preview
68/100- ECI154.8
- Price$2.00 / $12.00
- Context1.05M
Alibaba (Qwen)Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
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Make it a three-way comparison.
Gemini 3.1 Pro Preview is our pick
Gemini 3.1 Pro Preview is the better all-round choice, scoring 68/100 against Qwen3.6 Max Preview (54). It leads on capability, inputs & features and context window. Qwen3.6 Max Preview wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemini 3.1 Pro PreviewCapabilities Index (ECI): Gemini 3.1 Pro Preview 154.8 · Qwen3.6 Max Preview 149.2
- Lowest priceQwen3.6 Max PreviewQwen3.6 Max Preview $2.92 · Gemini 3.1 Pro Preview $4.50 per 1M tokens (3:1 blend)
- Longest contextGemini 3.1 Pro PreviewGemini 3.1 Pro Preview 1,048,576 · Qwen3.6 Max Preview 262,144 tokens
- Widest inputsGemini 3.1 Pro PreviewGemini 3.1 Pro Preview: Text, Images, PDFs, Audio, Video · Qwen3.6 Max Preview: Text
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Gemini 3.1 Pro Preview | Qwen3.6 Max Preview |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 77 |
| Price | 25% | 19 | 28 |
| Inputs & features | 15% | 100 | 35 |
| Context window | 10% | 61 | 37 |
| Overall | 100% | 68/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 3.1 Pro PreviewGoogle | Qwen3.6 Max PreviewAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 154.8 (best) | 149.2 |
| ECI rank | #31 of 148 (best) | #54 of 148 |
| GPQA DiamondGraduate-level science questions | 94.4% (best) | 87.4% |
| FrontierMath Tiers 1–3Research-level mathematics | 59.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 95.6% (best) | 91.1% |
| SWE-bench VerifiedFixing real GitHub issues | 75.6% | 76.7% (best) |
| SimpleQA VerifiedShort factual questions | 73.5% (best) | 52.0% |
| Price per million tokens | ||
| Input | $2.00 | $1.30 (best) |
| Output | $12.00 | $7.80 (best) |
| Cached input | $0.20 | $0.13 (best) |
| Blended (3:1) | $4.50 | $2.92 (best) |
| Long-context rate | Over 200K: $4.00 / $18.00 | Same rate |
| Price source | Official Google API | Official Alibaba API |
| Limits | ||
| Context window | 1,048,576 tokens (best) | 262,144 tokens |
| Max output | 65,536 tokens | 65,536 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | Yes | No |
| Video | Yes | No |
| Reasoning | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | gemini-3.1-pro-preview | qwen3.6-max-preview |
| API providers | 26 (best) | 10 |
| Released | Feb 19, 2026 | Apr 20, 2026 |
| Knowledge cutoff | Jan 2025 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 3.1 Pro Preview$44.00
- Qwen3.6 Max Preview$28.60
Which should you choose?
Which is better: Gemini 3.1 Pro Preview or Qwen3.6 Max Preview?
Gemini 3.1 Pro Preview is the better all-round choice, scoring 68/100 against Qwen3.6 Max Preview (54). It leads on capability, inputs & features and context window. Qwen3.6 Max Preview wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 3.1 Pro Preview or Qwen3.6 Max Preview?
Qwen3.6 Max Preview is cheaper at $1.30 input / $7.80 output per million tokens (official Alibaba API price). Gemini 3.1 Pro Preview costs $2.00 input / $12.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $2.92 per million tokens for Qwen3.6 Max Preview versus $4.50 for Gemini 3.1 Pro Preview (1.5× as much).
Which scores higher on benchmarks?
Gemini 3.1 Pro Preview scores higher on the Capabilities Index (ECI): Gemini 3.1 Pro Preview 154.8 (#31 of 148) and Qwen3.6 Max Preview 149.2 (#54 of 148). Their confidence ranges do not overlap (152.6–157.3 vs 147.6–152.0), so the gap is a real one. On individual benchmarks: GPQA Diamond — Gemini 3.1 Pro Preview 94.4%, Qwen3.6 Max Preview 87.4%; OTIS Mock AIME 2024–2025 — Gemini 3.1 Pro Preview 95.6%, Qwen3.6 Max Preview 91.1%; SWE-bench Verified — Qwen3.6 Max Preview 76.7%, Gemini 3.1 Pro Preview 75.6%; SimpleQA Verified — Gemini 3.1 Pro Preview 73.5%, Qwen3.6 Max Preview 52.0%.
Which is better for coding?
Qwen3.6 Max Preview resolves more real GitHub issues on SWE-bench Verified: Qwen3.6 Max Preview 76.7% and Gemini 3.1 Pro Preview 75.6%. Both support tool calling for agent workflows.
Which has the bigger context window?
Gemini 3.1 Pro Preview has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.6 Max Preview. Maximum output per response: Gemini 3.1 Pro Preview up to 65,536, Qwen3.6 Max Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini 3.1 Pro Preview accepts text, images, PDFs, audio and video; Qwen3.6 Max Preview accepts text. Gemini 3.1 Pro Preview handles the widest range of inputs.
Are any of these open source?
No. Gemini 3.1 Pro Preview and Qwen3.6 Max Preview are proprietary and only available through APIs and apps.
Which is newer?
Qwen3.6 Max Preview is the newest, released Apr 20, 2026. Gemini 3.1 Pro Preview came out Feb 19, 2026. Knowledge cutoff: Gemini 3.1 Pro Preview Jan 2025, Qwen3.6 Max Preview Apr 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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