Gemini 3.1 Pro Preview vs Qwen3.8 Max
Too close to call on our weighted score (Qwen3.8 Max 69, Gemini 3.1 Pro Preview 68). The right pick depends on what you value most.
GoogleGemini 3.1 Pro Preview
68/100- ECI154.8
- Price$2.00 / $12.00
- Context1.05M
Alibaba (Qwen)Qwen3.8 Max
69/100- ECI156.6
- Price$2.00 / $6.00
- Context1M
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (Qwen3.8 Max 69/100, Gemini 3.1 Pro Preview 68/100), so choose by what matters most for your work: Qwen3.8 Max for raw capability and Gemini 3.1 Pro Preview for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.8 MaxCapabilities Index (ECI): Qwen3.8 Max 156.6 · Gemini 3.1 Pro Preview 154.8
- Lowest priceQwen3.8 MaxQwen3.8 Max $3.00 · 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 · Qwen3.8 Max 1,000,000 tokens
- Widest inputsGemini 3.1 Pro PreviewGemini 3.1 Pro Preview: Text, Images, PDFs, Audio, Video · Qwen3.8 Max: Text, Images, PDFs, Video
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Gemini 3.1 Pro Preview | Qwen3.8 Max |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 86 |
| Price | 25% | 19 | 27 |
| Inputs & features | 15% | 100 | 90 |
| Context window | 10% | 61 | 60 |
| Overall | 100% | 68/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 3.1 Pro PreviewGoogle | Qwen3.8 MaxAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 154.8 | 156.6 (best) |
| ECI rank | #31 of 148 | #20 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 94.4% (best) | 92.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 59.7% | 74.7% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 95.6% | 99.4% (best) |
| SWE-bench VerifiedFixing real GitHub issues | 75.6% | — |
| SimpleQA VerifiedShort factual questions | 73.5% (best) | 45.8% |
| Price per million tokens | ||
| Input | $2.00 | $2.00 |
| Output | $12.00 | $6.00 (best) |
| Cached input | $0.20 (best) | $0.25 |
| Blended (3:1) | $4.50 | $3.00 (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) | 1,000,000 tokens |
| Max output | 65,536 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | Yes |
| Audio | Yes | No |
| Video | Yes | Yes |
| Reasoning | Yeslow · medium · high | Yeslow · medium · xhigh |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | gemini-3.1-pro-preview | qwen3.8-max |
| API providers | 26 (best) | 25 |
| Released | Feb 19, 2026 | Aug 3, 2026 |
| Knowledge cutoff | 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.
- Gemini 3.1 Pro Preview$44.00
- Qwen3.8 Max$32.00
Which should you choose?
Which is better: Gemini 3.1 Pro Preview or Qwen3.8 Max?
It is close. Our weighted score puts them within 2 points (Qwen3.8 Max 69/100, Gemini 3.1 Pro Preview 68/100), so choose by what matters most for your work: Qwen3.8 Max for raw capability and Gemini 3.1 Pro Preview for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 3.1 Pro Preview or Qwen3.8 Max?
Qwen3.8 Max is cheaper at $2.00 input / $6.00 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 $3.00 per million tokens for Qwen3.8 Max versus $4.50 for Gemini 3.1 Pro Preview (1.5× as much).
Which scores higher on benchmarks?
Qwen3.8 Max scores higher on the Capabilities Index (ECI): Qwen3.8 Max 156.6 (#20 of 148) and Gemini 3.1 Pro Preview 154.8 (#31 of 148). The confidence ranges of the top two overlap (154.5–158.8 vs 152.6–157.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemini 3.1 Pro Preview 94.4%, Qwen3.8 Max 92.7%; FrontierMath Tiers 1–3 — Qwen3.8 Max 74.7%, Gemini 3.1 Pro Preview 59.7%; OTIS Mock AIME 2024–2025 — Qwen3.8 Max 99.4%, Gemini 3.1 Pro Preview 95.6%; SimpleQA Verified — Gemini 3.1 Pro Preview 73.5%, Qwen3.8 Max 45.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.8 Max yet, so there is no like-for-like coding score. On overall capability, Qwen3.8 Max leads, which tends to carry over to coding, but test on your own codebase. 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 1,000,000 for Qwen3.8 Max. Maximum output per response: Gemini 3.1 Pro Preview up to 65,536, Qwen3.8 Max up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Gemini 3.1 Pro Preview accepts text, images, PDFs, audio and video; Qwen3.8 Max accepts text, images, PDFs and video. Gemini 3.1 Pro Preview handles the widest range of inputs.
Are any of these open source?
No. Gemini 3.1 Pro Preview and Qwen3.8 Max are proprietary and only available through APIs and apps.
Which is newer?
Qwen3.8 Max is the newest, released Aug 3, 2026. Gemini 3.1 Pro Preview came out Feb 19, 2026. Knowledge cutoff: Gemini 3.1 Pro Preview 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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