Gemini 3.5 Flash-LitevsMistral Medium 3.5
Gemini 3.5 Flash-Lite | Mistral Medium 3.5 | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | — | 128B |
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. | — | 256k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $0.30 | $1.50 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $2.50 | $7.50 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.03 | — |
| BenchmarksPublished by one model only | ||
BullshitBench v2Nonsense detection — Given 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. | 66% | — |
SWE-Bench ProAgentic coding — Can 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. | 54.2% | — |
SWE-Bench VerifiedCoding — Real 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. | — | 77.6% |
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. | 54% | — |
BU BenchBrowser agent — Can 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. | 49% | — |
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 74% | — |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | 1140 | — |
| Overview | ||
| Company | Mistral | |
| Release date | Jul 21 2026 | Apr 29 2026 |
| Access | Proprietary | Open Weight |
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Frequently asked questions
Gemini 3.5 Flash-Lite and Mistral Medium 3.5 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 3.5 Flash-Lite is cheaper on both input and output: $0.30 vs $1.50 per million input tokens, and $2.50 vs $7.50 per million output tokens. Mistral Medium 3.5 shipped 83 days before Gemini 3.5 Flash-Lite, so benchmark comparisons should account for the intervening progress.
Gemini 3.5 Flash-Lite is proprietary, while Mistral Medium 3.5 is open weight.
Direct benchmark comparisons are unavailable — Gemini 3.5 Flash-Lite and Mistral Medium 3.5 don't publish scores on any of the same benchmarks.