Claude Opus 4.8 vs Gemini 3.1 Pro: Which Wins?
Benchmark comparison of Claude Opus 4.8 and Gemini 3.1 Pro across coding, reasoning, knowledge, and web browsing. See where each model leads and which to choose.
Claude Opus 4.8 and Gemini 3.1 Pro both sit at the top of the leaderboard, but they pull ahead of each other in very different places. This post walks through the numbers category by category so you can make an informed decision.
Coding and agentic tasks: Opus 4.8 by a wide margin
The biggest gap between these two models is on real-world software engineering. SWE-bench Pro — the hardest agentic coding eval, built from genuine open-source GitHub issues — shows Opus 4.8 at 69.2% versus Gemini 3.1 Pro at 54.2%. That is a 15-point lead, the largest single gap in this comparison. On SWE-bench Verified the story is similar: Opus 4.8 at 88.6% versus Gemini's 80.6%.
For teams building AI coding assistants or autonomous pull-request agents, Opus 4.8 is clearly stronger. See the best LLM for coding in 2026 for a broader field comparison that includes GPT-5.5 and Mythos Preview.
Reasoning: Gemini edges GPQA, Opus leads the frontier
On GPQA Diamond — a graduate-level science benchmark covering physics, chemistry, and biology at PhD difficulty — Gemini 3.1 Pro scores 94.3% versus Opus 4.8's 93.6%. The 0.7-point difference is real but small; both models are performing at a very high level on this eval.
Humanity's Last Exam is a better discriminator at the frontier. Opus 4.8 reaches 49.8% without tools and 57.9% with tools. Gemini 3.1 Pro scores 44.4% without tools and 51.4% with tools — a consistent 5-6 point gap in Opus 4.8's favour on the hardest tasks. For a full reasoning analysis, read the best LLM for reasoning in 2026.
Broad knowledge: Gemini leads MMMLU
MMMLU is a massively multilingual knowledge benchmark covering dozens of languages and academic domains. Gemini 3.1 Pro scores 92.6%— ahead of Opus 4.7's 91.5% (Opus 4.8 is not reported on this benchmark). GPT-5.5 scores 83.2%, well behind both. If broad factual knowledge or multilingual coverage is your primary need, Gemini 3.1 Pro has a genuine advantage.
Web browsing and search
BrowseComp tests a model's ability to answer hard factual questions by browsing the web. Gemini 3.1 Pro scores 85.9%, slightly ahead of Opus 4.8's 84.3%. The gap is narrow — about 1.6 points — but Gemini has consistently strong web-grounding performance across evals, likely because of its native integration with Google Search infrastructure.
Computer use and tool calling
Opus 4.8 leads on both computer-use evals: OSWorld-Verified (83.4% vs 76.2%) and MCP-Atlas (82.2% vs 78.2%). These benchmarks test a model's ability to control a real desktop and call external tools correctly — critical capabilities for agentic products. See the live benchmark comparison to explore these numbers interactively.
Head-to-head summary
| Benchmark | Opus 4.8 | Gemini 3.1 Pro | Winner |
|---|---|---|---|
| SWE-bench Pro | 69.2% | 54.2% | Opus 4.8 |
| SWE-bench Verified | 88.6% | 80.6% | Opus 4.8 |
| GPQA Diamond | 93.6% | 94.3% | Gemini 3.1 Pro |
| HLE (with tools) | 57.9% | 51.4% | Opus 4.8 |
| BrowseComp | 84.3% | 85.9% | Gemini 3.1 Pro |
| MCP-Atlas | 82.2% | 78.2% | Opus 4.8 |
| OSWorld-Verified | 83.4% | 76.2% | Opus 4.8 |
| MMMLU | n/a | 92.6% | Gemini 3.1 Pro |
The verdict
- Choose Opus 4.8 for agentic coding, autonomous agents, computer use, tool calling, and frontier reasoning tasks.
- Choose Gemini 3.1 Pro for multilingual knowledge, web-grounded Q&A, and workloads where GPQA-style scientific reasoning is the primary signal.
- The coding gap — 15 points on SWE-bench Pro — is the single largest difference in this comparison and should be decisive for engineering teams.
- For a three-way view that adds GPT-5.5, see Opus 4.8 vs GPT-5.5 and the complete guide to LLM benchmarks.
