Gemini 3.7 Flashvsgpt-oss-20b
Gemini 3.7 Flash | gpt-oss-20b | |
|---|---|---|
| Specifications | ||
Parameters | — | 21B |
Context window | 1M | 128k |
| 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. | — | 60.7% |
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. | 65.3% | — |
Agentic coding FrontierCode v1.1 (Main) · main splitA set of very hard, frontier-difficulty coding tasks an AI agent has to complete end to end. The score is the share of tasks in the main split it solves. Higher is better. | 43.6% | — |
Agentic terminal coding Terminal-Bench 3.0command-line task completion (v3.0, much harder task set) | 14.9% | — |
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. | 85.8% | — |
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. | — | 10.9% |
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. | — | 17.3% |
Multidisciplinary reasoning Humanity's Last Exam (Verified)The re-checked edition of Humanity's Last Exam: the same extremely hard expert questions, minus the ones found to be flawed or wrongly answered. Scores on it run lower than on the original exam, so read the two as separate tests rather than a before-and-after. Higher is better. | 53.6% | — |
Biology BioMysteryBench · hardReal unsolved-style biology puzzles — the AI has to reason its way to an answer the way a research biologist would. The “hard” split contains the toughest cases. Higher is better. | 43.5% | — |
Biology BioMysteryBench · human solvedReal biology puzzles that human experts have managed to crack — can the AI reach the same answers? Higher is better. | 87.1% | — |
Biology LAB-Bench 2Everyday tasks from a working biology lab — reading protocols, interpreting figures and sequence data, and answering the practical questions a researcher hits at the bench. Higher is better. | 82.1% | — |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 71.5% |
General knowledge MMLUA 57-subject multiple-choice exam — history, law, medicine, maths — that was the standard measure of how much a model knows from 2020 until roughly 2024, when frontier scores crowded into the high 80s and labs moved on to harder tests. The scores here were published years apart under different testing setups, so read them as a historical record rather than a like-for-like ranking. Higher is better. | — | 85.3% |
Agentic computer use OSWorld 2.0Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Version 2.0 is a harder, refreshed task set. Higher is better. | 38.1% | — |
Agentic computer use Agent's Last ExamA hard set of desktop and operating-system tasks an AI agent has to finish by looking at the screen and working the machine itself. The score is the share it passes outright — partial credit does not count. Higher is better. | 26.3% | — |
Business workflows AutomationBenchTests whether the AI can run real multi-step business workflows — the kind of end-to-end office processes companies want to automate — from start to finish. Higher is better. | 30.4% | — |
Agentic legal work Harvey's Legal Agent BenchmarkHarvey's test of whether an AI agent can complete real legal work — drafting and reviewing documents, working with spreadsheets and presentations, and navigating files the way a lawyer's assistant would. Higher is better. | 90.7% | — |
Overall intelligence AA Intelligence IndexArtificial Analysis composite intelligence index across evals | 56 | — |
Knowledge work GDPval-AA v2economically valuable knowledge work (v2, re-based Elo) | 1525 | — |
Chart reasoning CharXiv ReasoningCan the AI read and reason about complex charts and figures, not just text? Higher is better. | 84.5% | — |
Document comprehension GDP.PDFReal professional PDFs — filings, reports, technical documents — with questions an expert in that field would ask. Tests whether the AI reads the page as a document, layout and figures included, rather than as loose text. Higher is better. | 34% | — |
Video understanding LVBenchCan the AI follow a very long video — up to an hour — and answer questions that need details from far apart in it? Higher is better. | 85.4% | — |
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. | 97% | — |
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. | 62.5% | — |
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. | 1588 | — |
| Overview | ||
| Company | OpenAI | |
| Release date | Aug 13 2026 | Aug 5 2025 |
| Access | Proprietary | Open Weight |
Which is better: Gemini 3.7 Flash or gpt-oss-20b?
Gemini 3.7 Flash and gpt-oss-20b don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. gpt-oss-20b shipped 373 days before Gemini 3.7 Flash, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Gemini 3.7 Flash) vs 128k (gpt-oss-20b). Gemini 3.7 Flash is proprietary, while gpt-oss-20b is open weight.
Direct benchmark comparisons are unavailable — Gemini 3.7 Flash and gpt-oss-20b don't publish scores on any of the same benchmarks.
Frequently asked questions
Gemini 3.7 Flash was released by Google on Aug 13 2026.
gpt-oss-20b was released by OpenAI on Aug 5 2025.
Gemini 3.7 Flash has a 1M context window; gpt-oss-20b has 128k.
Gemini 3.7 Flash is a proprietary model released by Google. gpt-oss-20b is an open weight model released by OpenAI.
Other comparisons
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