Gemini 2.5 Pro vs o3 vs Qwen3.5 Plus
Qwen3.5 Plus comes out ahead, 66 to 63 and 58 on our weighted score, and it is the cheaper option too.
GoogleGemini 2.5 Pro
63/100- ECI145.3
- Price$1.25 / $10.00
- Context1.05M
OpenAIo3
58/100- ECI146.9
- Price$2.00 / $8.00
- Context200K
- Our pick
Alibaba (Qwen)Qwen3.5 Plus
66/100- ECI146.8
- Price$0.40 / $2.40
- Context1M
Qwen3.5 Plus is our pick
Qwen3.5 Plus is the better all-round choice, scoring 66/100 against Gemini 2.5 Pro (63) and o3 (58). It leads on price. Gemini 2.5 Pro wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo3Capabilities Index (ECI): o3 146.9 · Qwen3.5 Plus 146.8 · Gemini 2.5 Pro 145.3
- Lowest priceQwen3.5 PlusQwen3.5 Plus $0.90 · Gemini 2.5 Pro $3.44 · o3 $3.50 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · Qwen3.5 Plus 1,000,000 · o3 200,000 tokens
- Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · o3: Text, Images, PDFs · Qwen3.5 Plus: Text, Images, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini 2.5 Pro | o3 | Qwen3.5 Plus |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 72 | 74 | 74 |
| Price | 25% | 24 | 24 | 52 |
| Inputs & features | 15% | 100 | 80 | 70 |
| Context window | 10% | 61 | 32 | 60 |
| Overall | 100% | 63/100 | 58/100 | 66/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 ProGoogle | o3OpenAI | Qwen3.5 PlusAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 145.3 | 146.9 (best) | 146.8 |
| ECI rank | #78 of 148 | #63 of 148 (best) | #65 of 148 |
| GPQA DiamondGraduate-level science questions | 85.3% (best) | 81.8% | 84.9% |
| FrontierMath Tiers 1–3Research-level mathematics | 24.6% | 33.3% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 84.7% | 84.4% | 86.7% (best) |
| SWE-bench VerifiedFixing real GitHub issues | 57.6% | 62.3% (best) | — |
| SimpleQA VerifiedShort factual questions | — | 49.4% (best) | 25.4% |
| Price per million tokens | |||
| Input | $1.25 | $2.00 | $0.40 (best) |
| Output | $10.00 | $8.00 | $2.40 (best) |
| Cached input | $0.125 (best) | $0.50 | — |
| Blended (3:1) | $3.44 | $3.50 | $0.90 (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) | 200,000 tokens | 1,000,000 tokens |
| Max output | 65,536 tokens | 100,000 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | No |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yes | Yeslow · 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 | o3 | qwen3.5-plus |
| API providers | 22 (best) | 18 | 10 |
| Released | Jun 17, 2025 | Apr 16, 2025 | Feb 16, 2026 |
| Knowledge cutoff | Jan 2025 | May 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
- o3$36.00
- Qwen3.5 Plus$8.80
Which should you choose?
Which is better: Gemini 2.5 Pro, o3 or Qwen3.5 Plus?
Qwen3.5 Plus is the better all-round choice, scoring 66/100 against Gemini 2.5 Pro (63) and o3 (58). It leads on price. Gemini 2.5 Pro wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 2.5 Pro, o3 or Qwen3.5 Plus?
Qwen3.5 Plus is cheaper at $0.40 input / $2.40 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); o3 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.90 per million tokens for Qwen3.5 Plus versus $3.44 for Gemini 2.5 Pro (3.8× as much) and $3.50 for o3 (3.9× as much).
Which scores higher on benchmarks?
o3 scores higher on the Capabilities Index (ECI): o3 146.9 (#63 of 148), Qwen3.5 Plus 146.8 (#65 of 148) and Gemini 2.5 Pro 145.3 (#78 of 148). The confidence ranges of the top two overlap (144.9–148.6 vs 144.6–148.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemini 2.5 Pro 85.3%, Qwen3.5 Plus 84.9%, o3 81.8%; OTIS Mock AIME 2024–2025 — Qwen3.5 Plus 86.7%, Gemini 2.5 Pro 84.7%, o3 84.4%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 Plus yet, so there is no like-for-like coding score. On overall capability, o3 leads, which tends to carry over to coding, but test on your own codebase. 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 1,000,000 for Qwen3.5 Plus and 200,000 for o3. Maximum output per response: Gemini 2.5 Pro up to 65,536, o3 up to 100,000, Qwen3.5 Plus up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Pro accepts text, images, PDFs, audio and video; o3 accepts text, images and PDFs; Qwen3.5 Plus accepts text, images and video. Gemini 2.5 Pro handles the widest range of inputs.
Are any of these open source?
No. Gemini 2.5 Pro, o3 and Qwen3.5 Plus are proprietary and only available through APIs and apps.
Which is newer?
Qwen3.5 Plus is the newest, released Feb 16, 2026. Gemini 2.5 Pro came out Jun 17, 2025; o3 came out Apr 16, 2025. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, o3 May 2024, Qwen3.5 Plus 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.
