Gemini 3.0 ProvsQwen3.5
Gemini 3.0 Pro | Qwen3.5 | |
|---|---|---|
| Specifications | ||
Parameters | — | 397B |
Context window | — | 1M |
| Benchmarks | ||
Coding SWE-Bench VerifiedReal coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 76.2% | 76.4%Best |
Multilingual coding SWE-Bench MultilingualLike SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. | — | 69.3% |
Next.js coding Next.js EvalsVercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 67% | — |
Agentic terminal coding Terminal-Bench 2.0Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | — | 52.5% |
Web browsing BrowseCompCan the AI browse the web and track down hard-to-find answers? Higher is better. | — | 69% |
Multidisciplinary reasoning Humanity's Last Exam · no toolsHumanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | — | 28.7% |
Abstract reasoning ARC-AGI-2Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | 31.1% | — |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 91.9%Best | 88.4% |
Agentic computer use OSWorld-VerifiedCan the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | — | 62.2% |
Chart reasoning CharXiv ReasoningCan the AI read and reason about complex charts and figures, not just text? Higher is better. | — | 80.8% |
Multimodal reasoning MMMU-ProA tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | — | 79% |
Multimodal MMMUTests the AI on understanding images and text together across many college subjects. Higher is better. | 81% | 85%Best |
Community preference Arena Elo (Text)Real people chat with two anonymous AIs side by side and vote for the answer they prefer. Votes become a chess-style Elo rating on arena.ai — it measures which AI people actually like, not test scores. Higher is better. | 1486 | — |
Community preference (code) Arena Elo (Code)Like the text arena, but people vote on which AI writes better code. The votes become a chess-style Elo rating on arena.ai. Higher is better. | 1439 | — |
| Overview | ||
| Company | Qwen | |
| Release date | Nov 18 2025 | Feb 16 2026 |
| Access | Proprietary | Open Weight |
Which is better: Gemini 3.0 Pro or Qwen3.5?
Qwen3.5 leads Gemini 3.0 Pro on 2 of the 3 benchmarks they both report (SWE-Bench Verified, GPQA Diamond, MMMU). Gemini 3.0 Pro shipped 90 days before Qwen3.5, so benchmark comparisons should account for the intervening progress.
Gemini 3.0 Pro is proprietary, while Qwen3.5 is open weight.
On SWE-Bench Verified, Qwen3.5 leads at 76.4% vs Gemini 3.0 Pro at 76.2%. On GPQA Diamond, Gemini 3.0 Pro leads at 91.9% vs Qwen3.5 at 88.4%. On MMMU, Qwen3.5 leads at 85% vs Gemini 3.0 Pro at 81%.
Frequently asked questions
Gemini 3.0 Pro was released by Google on Nov 18 2025.
Qwen3.5 was released by Qwen on Feb 16 2026.
Qwen3.5 leads on SWE-Bench Verified — Gemini 3.0 Pro 76.2% vs Qwen3.5 76.4%.
Gemini 3.0 Pro leads on GPQA Diamond — Gemini 3.0 Pro 91.9% vs Qwen3.5 88.4%.
Gemini 3.0 Pro is a proprietary model released by Google. Qwen3.5 is an open weight model released by Qwen.