Gemini 3.5 FlashvsGPT-5.6 Terra
Gemini 3.5 Flash | GPT-5.6 Terra | |
|---|---|---|
| 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. | 20% | 53%Best |
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. | 14.1%Best | 5.4% |
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. | 54.2%Best | 26% |
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. | 60.5%Best | 30.4% |
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. | 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. | 48.8% | 64.9%Best |
Agentic coding CursorBench v3.1Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | 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% | — |
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. | — | 20.8% |
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. | 76.2% | 84.3%Best |
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% | — |
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. | 40.2% | — |
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. | 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. | 1656 | — |
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. | 1476Best | 1467 |
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. | 1509 | 1526Best |
| Overview | ||
| Company | OpenAI | |
| Release date | May 19 2026 | Jun 26 2026 |
| Access | Proprietary | Proprietary |
Which is better: Gemini 3.5 Flash or GPT-5.6 Terra?
GPT-5.6 Terra leads Gemini 3.5 Flash on 7 of the 8 benchmarks they both report. Gemini 3.5 Flash shipped 38 days before GPT-5.6 Terra, 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, GPT-5.6 Terra leads at 53% vs Gemini 3.5 Flash at 20%. On Gray Swan IPI · k = 1, GPT-5.6 Terra leads at 5.4% vs Gemini 3.5 Flash at 14.1%. On Gray Swan IPI · k = 10, GPT-5.6 Terra leads at 26% vs Gemini 3.5 Flash at 54.2%. On Gray Swan IPI · k = 15, GPT-5.6 Terra leads at 30.4% vs Gemini 3.5 Flash at 60.5%. On CursorBench v3.2, GPT-5.6 Terra leads at 64.9% vs Gemini 3.5 Flash at 48.8%. On Terminal-Bench 2.1, GPT-5.6 Terra leads at 84.3% vs Gemini 3.5 Flash at 76.2%. On Arena Elo (Text), Gemini 3.5 Flash leads at 1476 vs GPT-5.6 Terra at 1467. On Arena Elo (Code), GPT-5.6 Terra leads at 1526 vs Gemini 3.5 Flash at 1509.
Frequently asked questions
Gemini 3.5 Flash was released by Google on May 19 2026.
GPT-5.6 Terra was released by OpenAI on Jun 26 2026.
GPT-5.6 Terra leads on CursorBench v3.2 — Gemini 3.5 Flash 48.8% vs GPT-5.6 Terra 64.9%.
Other comparisons
Gemini 3.5 FlashvsClaude Opus 5GPT-5.6 TerravsClaude Opus 5Gemini 3.5 FlashvsMuse GlimmerGPT-5.6 TerravsMuse GlimmerGemini 3.5 FlashvsGrok 4.5GPT-5.6 TerravsGrok 4.5Gemini 3.5 FlashvsDeepSeek-V4-Flash-0731GPT-5.6 TerravsDeepSeek-V4-Flash-0731Gemini 3.5 FlashvsMistral Medium 3.5GPT-5.6 TerravsMistral Medium 3.5Gemini 3.5 FlashvsKimi K3GPT-5.6 TerravsKimi K3