Gemini 3.5 Flash Lite vs GPT-5 Mini
At a Glance
| Compare |  Gemini 3.5 Flash LiteGoogle DeepMind |  GPT-5 MiniOpenAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #39 of 4617.6 score · 3/3 sources · complete | #45 of 460.0 score · 2/3 sources · provisional · missing LiveBench · full-core range 0.0–33.4 |
| CostLower is better · Published-token output estimate | #8 of 44$0.029 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #32 of 3846.2 score · 3/3 sources · complete | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.30Google AI ↗ · Aug 29, 2026 | $0.125Openrouter ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $2.50Google AI ↗ · Aug 29, 2026 | $1.00Openrouter ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 1,049K | 400K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 3, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Gemini 3.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| ARC-AGI-1verified-v1-ba05d69f6453 · verified_score · leader | 53.5098% of row best · percent · Gemini 3.5 Flash-Lite (High) | 54.33100% of row best · percent · GPT-5 Mini (High) |
| ARC-AGI-2verified-v2-6c676fa3e9af · verified_score · leader | 10.28100% of row best · percent · Gemini 3.5 Flash-Lite (High) | 4.4443% of row best · percent · GPT-5 Mini (High) |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,435.54100% of row best · rating · gemini-3.5-flash-lite; 95% CI [1430.59505493, 1440.49024696]; votes 26165; rank 79 | 1,372.9696% of row best · rating · gpt-5-mini-high; 95% CI [1368.38533638, 1377.53632183]; votes 26569; rank 166 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,268.42100% of row best · rating · gemini-3.5-flash-lite; 95% CI [1258.88097193, 1277.96729164]; votes 5254; rank 37 | 1,201.9095% of row best · rating · gpt-5-mini-high; 95% CI [1194.06379328, 1209.74466964]; votes 28970; rank 78 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 73.4297% of row best · points · Gemini 3.5 Flash-Lite · 1,966 output tokens / case | 76.07100% of row best · points · GPT-5 mini · 3,925 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 3 benchmark winsOverall lead | 1 benchmark win |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Gemini 3.5 Flash-Lite | GPT-5 Mini |
|---|---|---|
| Developer | Google DeepMind | OpenAI |
| Family | Gemini 3 | Gpt 5 |
| Model | Gemini 3.5 Flash-Lite | GPT-5 Mini |
| Version | Gemini 3.5 Flash-Lite | GPT-5 Mini |
| Lifecycle | active | active |
| Released | Unknown | 2025-08-07 |
| Knowledge cutoff | Unknown | 2024-05-31 |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 400K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
Gemini 3.5 Flash Lite Capabilities
GPT-5 Mini Capabilities
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Gemini 3.5 Flash-LiteGoogle DeepMind | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini 3.5 Flash Lite vs GPT-5 Mini FAQs
Is Gemini 3.5 Flash Lite or GPT-5 Mini better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.5 Flash Lite and GPT-5 Mini, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3.5 Flash Lite or GPT-5 Mini?+
Gemini 3.5 Flash Lite is $0.30 and GPT-5 Mini is $0.125 per million tokens, so GPT-5 Mini is cheaper on this metric. Gemini 3.5 Flash Lite is $2.50 and GPT-5 Mini is $1.00 per million tokens, so GPT-5 Mini is cheaper on this metric.
Which has a larger context window, Gemini 3.5 Flash Lite or GPT-5 Mini?+
Gemini 3.5 Flash Lite has the larger sourced context window. Gemini 3.5 Flash Lite supports 1,049K and GPT-5 Mini supports 400K.
Which performs better in benchmarks, Gemini 3.5 Flash Lite or GPT-5 Mini?+
Gemini 3.5 Flash Lite leads the current overall benchmark count. The result uses 4 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Gemini 3.5 Flash Lite or GPT-5 Mini be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Gemini 3.5 Flash Lite is not marked open weight; GPT-5 Mini is not marked open weight.
Can Gemini 3.5 Flash Lite and GPT-5 Mini understand images?+
Gemini 3.5 Flash Lite is documented with image input; GPT-5 Mini is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 3.5 Flash Lite or GPT-5 Mini?+
GPT-5 Mini has the larger sourced maximum output: Gemini 3.5 Flash Lite supports 66K and GPT-5 Mini supports 128K output tokens.
Do Gemini 3.5 Flash Lite and GPT-5 Mini support reasoning and tool use?+
Gemini 3.5 Flash Lite: reasoning, tool calling, and image input. GPT-5 Mini: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 3.5 Flash Lite or GPT-5 Mini?+
Gemini 3.5 Flash Lite has 2 sourced provider routes; GPT-5 Mini has 2, a tie.
Which offers better value, Gemini 3.5 Flash Lite or GPT-5 Mini?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.