Claude Sonnet 5vsGemini 3.5 Flash
Claude Sonnet 5 | Gemini 3.5 Flash | |
|---|---|---|
| Benchmarks | ||
Nonsense detection BullshitBench v2Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 80%Best | 20% |
Prompt injection robustness Gray Swan IPI · k = 1Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. Gray Swan's indirect prompt injection benchmark measures how often such an attack succeeds when the attacker gets a single try. Lower is better. | 0.6% | 14.1%Best |
Prompt injection robustness Gray Swan IPI · k = 10Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. This variant gives the attacker 10 tries and counts an attack as successful if any of them works. Lower is better. | 4.7% | 54.2%Best |
Prompt injection robustness Gray Swan IPI · k = 15Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. This variant gives the attacker 15 tries and counts an attack as successful if any of them works. Lower is better. | 5.9% | 60.5%Best |
Agentic coding SWE-Bench ProCan the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | 63.2%Best | 55.1% |
Agentic coding CursorBench v3.2Cursor's own test of harder, real-world coding tasks inside a code editor, on the refreshed v3.2 task set. Scores aren't comparable with v3.1. Higher is better. | 61.5%Best | 48.8% |
Agentic coding CursorBench v3.1Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | 61.2%Best | 49.8% |
Agentic coding DeepSWE 1.1Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | — | 37% |
ML engineering MLE-BenchCan the AI do the work of a machine-learning engineer? It competes in real Kaggle competitions — building, training, and tuning models end to end — and the score reflects how well it places. Higher is better. | — | 49.7% |
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. | 79% | — |
Supabase coding Supabase Evals · with skillsSupabase's own open benchmark: a coding agent is dropped into a real Supabase project and asked to do real work — set up a schema, fix a broken security policy, debug an Edge Function — and every run is checked against a live Supabase stack. This is the headline number, where the agent has Supabase's own skills loaded, as most people building on Supabase would. The score is the share of scenarios it got right. Higher is better. | 95.5% | — |
Supabase coding Supabase Evals · no skillsThe same Supabase scenarios, but with none of Supabase's skills loaded — so it measures what the model already knows about building on Supabase, rather than how well it follows Supabase's supplied instructions. Higher is better. | 90.9% | — |
Agentic computer work Frontier-Bench v0.1A hard, ever-evolving set of real computer tasks — coding, system administration, data work, and more — that an AI agent has to complete on its own. Run by the Harbor / Laude Institute team as the successor to Terminal-Bench (v0.1 is the first release of the task set). The score is the share of tasks solved. Higher is better. | 14.6% | — |
Agentic terminal coding Terminal-Bench 2.1Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | 80.4%Best | 76.2% |
Multi-step tool use MCP AtlasCan the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better. | — | 83.6% |
General tool use ToolathlonTests how well the AI uses everyday real-world tools and apps to get things done. Higher is better. | — | 56.5% |
Browser agent BU BenchCan the AI drive a real web browser to finish tasks — clicking, filling forms, and navigating sites the way a person would? Run by Browser Use on their BU Bench task set. Higher is better. | — | 58% |
Web browsing BrowseCompCan the AI browse the web and track down hard-to-find answers? Higher is better. | 84.7% | — |
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. | 43.2%Best | 40.2% |
Multidisciplinary reasoning Humanity's Last Exam · with toolsHumanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 57.4% | — |
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. | — | 72.1% |
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. | 81.2%Best | 78.4% |
Agentic financial analysis Finance Agent v2Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better. | — | 57.9% |
Knowledge work GDPval-AAMeasures how well the AI does economically valuable knowledge work, judged against human experts. Shown as a rating (like a chess Elo) — higher is better. | 1618 | 1656Best |
Knowledge work GDPval-AA v2economically valuable knowledge work (v2, re-based Elo) | — | 1349 |
Chart reasoning CharXiv ReasoningCan the AI read and reason about complex charts and figures, not just text? Higher is better. | — | 84.2% |
Multimodal reasoning MMMU-ProA tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | — | 83.6% |
Spatial reasoning Blueprint-Bench 2Can the AI reason about space and layout — for example, understanding a floor plan or blueprint? Higher is better. | — | 33.6% |
Long context MRCR v2 (8-needle) · 128k averageTests whether the AI can find specific details buried inside a very long document (around 128k tokens — roughly a long book). Higher is better. | — | 77.3% |
Long context MRCR v2 (8-needle) · 1M pointwiseTests whether the AI can find specific details buried inside an enormous document (around 1 million tokens — many books). Higher is better. | — | 26.6% |
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. | 1463 | 1476Best |
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. | 1543Best | 1509 |
| Overview | ||
| Company | Anthropic | |
| Release date | Jun 30 2026 | May 19 2026 |
| Access | Proprietary | Proprietary |
Which is better: Claude Sonnet 5 or Gemini 3.5 Flash?
Claude Sonnet 5 leads Gemini 3.5 Flash on 11 of the 13 benchmarks they both report. Gemini 3.5 Flash shipped 42 days before Claude Sonnet 5, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On BullshitBench v2, Claude Sonnet 5 leads at 80% vs Gemini 3.5 Flash at 20%. On Gray Swan IPI · k = 1, Claude Sonnet 5 leads at 0.6% vs Gemini 3.5 Flash at 14.1%. On Gray Swan IPI · k = 10, Claude Sonnet 5 leads at 4.7% vs Gemini 3.5 Flash at 54.2%. On Gray Swan IPI · k = 15, Claude Sonnet 5 leads at 5.9% vs Gemini 3.5 Flash at 60.5%. On SWE-Bench Pro, Claude Sonnet 5 leads at 63.2% vs Gemini 3.5 Flash at 55.1%. On CursorBench v3.2, Claude Sonnet 5 leads at 61.5% vs Gemini 3.5 Flash at 48.8%. On CursorBench v3.1, Claude Sonnet 5 leads at 61.2% vs Gemini 3.5 Flash at 49.8%. On Terminal-Bench 2.1, Claude Sonnet 5 leads at 80.4% vs Gemini 3.5 Flash at 76.2%. On Humanity's Last Exam · no tools, Claude Sonnet 5 leads at 43.2% vs Gemini 3.5 Flash at 40.2%. On OSWorld-Verified, Claude Sonnet 5 leads at 81.2% vs Gemini 3.5 Flash at 78.4%. On GDPval-AA, Gemini 3.5 Flash leads at 1656 vs Claude Sonnet 5 at 1618. On Arena Elo (Text), Gemini 3.5 Flash leads at 1476 vs Claude Sonnet 5 at 1463. On Arena Elo (Code), Claude Sonnet 5 leads at 1543 vs Gemini 3.5 Flash at 1509.
Frequently asked questions
Claude Sonnet 5 was released by Anthropic on Jun 30 2026.
Gemini 3.5 Flash was released by Google on May 19 2026.
Claude Sonnet 5 leads on SWE-Bench Pro — Claude Sonnet 5 63.2% vs Gemini 3.5 Flash 55.1%.
Claude Sonnet 5 leads on Humanity's Last Exam · no tools — Claude Sonnet 5 43.2% vs Gemini 3.5 Flash 40.2%.
Other comparisons
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