Gemini 2.5 Pro vs GPT-5 vs Qwen3.6 Max Preview
Gemini 2.5 Pro comes out ahead, 63 to 60 and 54 on our weighted score, though Qwen3.6 Max Preview is 15% cheaper per token.
- Our pick
GoogleGemini 2.5 Pro
63/100- ECI145.3
- Price$1.25 / $10.00
- Context1.05M
OpenAIGPT-5
60/100- ECI150.0
- Price$1.25 / $10.00
- Context400K
Alibaba (Qwen)Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
Gemini 2.5 Pro is our pick
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against GPT-5 (60) and Qwen3.6 Max Preview (54). It leads on 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%.
- CapabilityGPT-5Capabilities Index (ECI): GPT-5 150.0 · Qwen3.6 Max Preview 149.2 · Gemini 2.5 Pro 145.3
- Lowest priceQwen3.6 Max PreviewQwen3.6 Max Preview $2.92 · Gemini 2.5 Pro $3.44 · GPT-5 $3.44 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · GPT-5 400,000 · Qwen3.6 Max Preview 262,144 tokens
- Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · GPT-5: Text, Images · Qwen3.6 Max Preview: Text
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini 2.5 Pro | GPT-5 | Qwen3.6 Max Preview |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 72 | 78 | 77 |
| Price | 25% | 24 | 24 | 28 |
| Inputs & features | 15% | 100 | 70 | 35 |
| Context window | 10% | 61 | 44 | 37 |
| Overall | 100% | 63/100 | 60/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 ProGoogle | GPT-5OpenAI | Qwen3.6 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 145.3 | 150.0 (best) | 149.2 |
| ECI rank | #78 of 148 | #50 of 148 (best) | #54 of 148 |
| GPQA DiamondGraduate-level science questions | 85.3% | 86.2% | 87.4% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 24.6% | 55.4% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 84.7% | 91.4% (best) | 91.1% |
| SWE-bench VerifiedFixing real GitHub issues | 57.6% | 73.6% | 76.7% (best) |
| SimpleQA VerifiedShort factual questions | — | 50.1% | 52.0% (best) |
| Price per million tokens | |||
| Input | $1.25 (best) | $1.25 (best) | $1.30 |
| Output | $10.00 | $10.00 | $7.80 (best) |
| Cached input | $0.125 (best) | $0.125 (best) | $0.13 |
| Blended (3:1) | $3.44 | $3.44 | $2.92 (best) |
| Long-context rate | Over 200K: $2.50 / $15.00 | Same rate | Same rate |
| Price source | Official Google API | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 400,000 tokens | 262,144 tokens |
| Max output | 65,536 tokens | 128,000 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yesminimal · low · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gemini-2.5-pro | gpt-5 | qwen3.6-max-preview |
| API providers | 22 | 24 (best) | 10 |
| Released | Jun 17, 2025 | Aug 7, 2025 | Apr 20, 2026 |
| Knowledge cutoff | Jan 2025 | Sep 30, 2024 | 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 2.5 Pro$32.50
- GPT-5$32.50
- Qwen3.6 Max Preview$28.60
Which should you choose?
Which is better: Gemini 2.5 Pro, GPT-5 or Qwen3.6 Max Preview?
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against GPT-5 (60) and Qwen3.6 Max Preview (54). It leads on 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 2.5 Pro, GPT-5 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 2.5 Pro costs $1.25 input / $10.00 output per million tokens (official Google API price); GPT-5 costs $1.25 input / $10.00 output per million tokens (official OpenAI 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 $3.44 for Gemini 2.5 Pro (1.2× as much) and $3.44 for GPT-5 (1.2× as much).
Which scores higher on benchmarks?
GPT-5 scores higher on the Capabilities Index (ECI): GPT-5 150.0 (#50 of 148), Qwen3.6 Max Preview 149.2 (#54 of 148) and Gemini 2.5 Pro 145.3 (#78 of 148). On individual benchmarks: GPQA Diamond — Qwen3.6 Max Preview 87.4%, GPT-5 86.2%, Gemini 2.5 Pro 85.3%; OTIS Mock AIME 2024–2025 — GPT-5 91.4%, Qwen3.6 Max Preview 91.1%, Gemini 2.5 Pro 84.7%; SWE-bench Verified — Qwen3.6 Max Preview 76.7%, GPT-5 73.6%, 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%, GPT-5 73.6% 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 400,000 for GPT-5 and 262,144 for Qwen3.6 Max Preview. Maximum output per response: Gemini 2.5 Pro up to 65,536, GPT-5 up to 128,000, Qwen3.6 Max Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Pro accepts text, images, PDFs, audio and video; GPT-5 accepts text and images; Qwen3.6 Max Preview accepts text. Gemini 2.5 Pro handles the widest range of inputs.
Are any of these open source?
No. Gemini 2.5 Pro, GPT-5 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. GPT-5 came out Aug 7, 2025; Gemini 2.5 Pro came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, GPT-5 Sep 30, 2024, 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.
