Gemini 3.8 FlashvsCodestral Mamba 7B
Gemini 3.8 Flash | Codestral Mamba 7B | |
|---|---|---|
| Specifications | ||
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 1M | — |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.375Google | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $1.875Google | — |
| BenchmarksPublished by one model only | ||
DeepSWE 1.1Agentic coding — Artificial 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. | 71% | — |
Terminal-Bench 4.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Version 4.0 recalibrated how much time, CPU and memory each task gets, removed eight tasks and fixed nineteen, so fewer runs fail for reasons that have nothing to do with the model. Scores are not comparable with earlier versions. Higher is better. | 19.1% | — |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | 89.4% | — |
Humanity's Last Exam (Verified)Multidisciplinary reasoning — 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. | 54.9% | — |
BioMysteryBench · hardBiology — Real 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. | 56.5% | — |
BioMysteryBench · human solvedBiology — Real biology puzzles that human experts have managed to crack — can the AI reach the same answers? Higher is better. | 88.8% | — |
LAB-Bench 2Biology — Everyday 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. | 86.2% | — |
OSWorld 2.0Agentic computer use — Can 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. | 59% | — |
Finance Agent v2Agentic financial analysis — Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better. | 61.4% | — |
Harvey's Legal Agent BenchmarkAgentic legal work — Harvey'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. | 10% | — |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | 1545 | — |
CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better. | 86.2% | — |
GDP.PDFDocument comprehension — Real 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. | 35% | — |
LVBenchVideo understanding — Can 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. | 87.1% | — |
LVBench · agenticVideo understanding — The same long-video test, run with the AI free to navigate the video itself — skipping around, replaying sections — rather than being shown it once. Read it as a separate test from the unaided run above. Higher is better. | 87.8% | — |
| Overview | ||
| Company | Mistral | |
| Release date | Sep 2 2026 | Jul 16 2024 |
| Access | Proprietary | Open Weight |
Other comparisons
Gemini 3.8 FlashvsClaude Fable 5.1Codestral Mamba 7BvsClaude Fable 5.1Gemini 3.8 FlashvsGPT-6 AstraCodestral Mamba 7BvsGPT-6 AstraGemini 3.8 FlashvsMuse Spark 1.3Codestral Mamba 7BvsMuse Spark 1.3Gemini 3.8 FlashvsGrok 4.6Codestral Mamba 7BvsGrok 4.6Gemini 3.8 FlashvsDeepSeek-V4-Pro-0813Codestral Mamba 7BvsDeepSeek-V4-Pro-0813Gemini 3.8 FlashvsKimi K3Codestral Mamba 7BvsKimi K3
Frequently asked questions
Gemini 3.8 Flash and Codestral Mamba 7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral Mamba 7B shipped 778 days before Gemini 3.8 Flash, so benchmark comparisons should account for the intervening progress.
Gemini 3.8 Flash is proprietary, while Codestral Mamba 7B is open weight.
Direct benchmark comparisons are unavailable — Gemini 3.8 Flash and Codestral Mamba 7B don't publish scores on any of the same benchmarks.
Gemini 3.8 Flash was released by Google on Sep 2 2026.
Codestral Mamba 7B was released by Mistral on Jul 16 2024.
Gemini 3.8 Flash is a proprietary model released by Google. Codestral Mamba 7B is an open weight model released by Mistral.