Gemini 3 Flash vs Gemini 3.1 Pro
At a Glance
| Compare | Gemini 3 FlashGoogle DeepMind | Gemini 3.1 ProGoogle DeepMind |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #9 of 4679.7 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #27 of 44$0.161 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #9 of 3859.2 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.50Google AI ↗ · Aug 29, 2026 | $2.00Google AI ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $3.00Google AI ↗ · Aug 29, 2026 | $12.00Google AI ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,049K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 29, 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 Flash | Gemini 3.1 Pro |
|---|---|---|
| LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · leader | 1,412.9998% of row best · rating · gemini-3-flash; 95% CI [1403.58694998, 1422.40270038]; votes 7158; rank 40 | 1,443.92100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1438.69417039, 1449.14324048]; votes 49457; rank 31 |
| LMArena Search Arenasearch-2026-08-24-d25aabda0010 · arena_rating · leader | 1,198.0999% of row best · rating · gemini-3-flash-grounding; 95% CI [1193.35426288, 1202.82591975]; votes 149334; rank 15 | 1,210.46100% of row best · rating · gemini-3.1-pro-grounding; 95% CI [1205.32063396, 1215.60669852]; votes 113282; rank 9 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,442.4097% of row best · rating · gemini-3-flash (thinking-minimal); 95% CI [1439.30492660, 1445.49388279]; votes 85799; rank 61 | 1,480.08100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1476.92899018, 1483.22190450]; votes 106951; rank 16 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,265.3798% of row best · rating · gemini-3-flash (thinking-minimal); 95% CI [1259.84136462, 1270.89646969]; votes 34860; rank 41 | 1,295.61100% of row best · rating · gemini-3.1-pro-preview; 95% CI [1290.13797622, 1301.07924121]; votes 40691; rank 19 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 4 benchmark winsNo overall winner |
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 Flash | Gemini 3.1 Pro |
|---|---|---|
| Developer | Google DeepMind | Google DeepMind |
| Family | Gemini 3 | Gemini 3 |
| Model | Gemini 3 Flash | Gemini 3.1 Pro |
| Version | Gemini 3 Flash | Gemini 3.1 Pro |
| Lifecycle | preview | preview |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image, Video, Audio, Document |
| Output modalities | Text | Text |
| Context window | 1,049K | 1,049K |
| 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) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
Gemini 3 Flash Capabilities
Gemini 3.1 Pro Capabilities
Primary Evidence
Sources and Freshness
Questions
Gemini 3 Flash vs Gemini 3.1 Pro FAQs
Is Gemini 3 Flash or Gemini 3.1 Pro better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3 Flash and Gemini 3.1 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3 Flash or Gemini 3.1 Pro?+
Gemini 3 Flash is $0.50 and Gemini 3.1 Pro is $2.00 per million tokens, so Gemini 3 Flash is cheaper on this metric. Gemini 3 Flash is $3.00 and Gemini 3.1 Pro is $12.00 per million tokens, so Gemini 3 Flash is cheaper on this metric.
Which has a larger context window, Gemini 3 Flash or Gemini 3.1 Pro?+
Neither model has a larger sourced context window in this comparison. Gemini 3 Flash is 1,049K and Gemini 3.1 Pro is 1,049K.
Which performs better in benchmarks, Gemini 3 Flash or Gemini 3.1 Pro?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Gemini 3 Flash or Gemini 3.1 Pro be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Gemini 3 Flash is not marked open weight; Gemini 3.1 Pro is not marked open weight.
Can Gemini 3 Flash and Gemini 3.1 Pro understand images?+
Gemini 3 Flash is documented with image input; Gemini 3.1 Pro is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 3 Flash or Gemini 3.1 Pro?+
Neither has a larger sourced maximum output. Gemini 3 Flash is 66K and Gemini 3.1 Pro is 66K.
Do Gemini 3 Flash and Gemini 3.1 Pro support reasoning and tool use?+
Gemini 3 Flash: reasoning, tool calling, and image input. Gemini 3.1 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 3 Flash or Gemini 3.1 Pro?+
Gemini 3 Flash has 2 sourced provider routes; Gemini 3.1 Pro has 2, a tie.
Which offers better value, Gemini 3 Flash or Gemini 3.1 Pro?+
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.