Gemini 3 Flash vs Mistral Medium 3.5 128B
At a Glance
| Compare |  Gemini 3 FlashGoogle DeepMind |  Mistral Medium 3.5 128BMistral AI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.50Google AI ↗ · Aug 29, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $3.00Google AI ↗ · Aug 29, 2026 | Not reported |
| Context windowMaximum documented tokens | 1,049K | 262K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 28, 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 | Mistral-Medium-3.5-128B |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,442.40100% of row best · rating · gemini-3-flash (thinking-minimal); 95% CI [1439.30492660, 1445.49388279]; votes 85799; rank 61 | 1,420.5898% of row best · rating · mistral-medium-3.5; 95% CI [1414.04225396, 1427.11615611]; votes 10996; rank 104 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,265.37100% of row best · rating · gemini-3-flash (thinking-minimal); 95% CI [1259.84136462, 1270.89646969]; votes 34860; rank 41 | 1,222.0597% of row best · rating · mistral-medium-3.5; 95% CI [1212.30064904, 1231.79518832]; votes 5090; rank 71 |
| Overall ResultCounted from the protocol-matched rows above | 2 benchmark winsNo overall winner | 0 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 | Mistral-Medium-3.5-128B |
|---|---|---|
| Developer | Google DeepMind | Mistral AI |
| Family | Gemini 3 | Mistral Medium 3 5 128b |
| Model | Gemini 3 Flash | Mistral-Medium-3.5-128B |
| Version | Gemini 3 Flash | Mistral-Medium-3.5-128B |
| Lifecycle | preview | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 262K |
| Total parameters | Unknown | 127.7B |
| Active parameters | Unknown | Unknown |
| License | Unknown | other |
| Open weights | No | Yes |
| API available | Yes | Unknown |
| Self-hostable | No | Yes |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
Gemini 3 Flash Capabilities
Mistral Medium 3.5 128B Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Gemini 3 FlashGoogle DeepMind | vs |  GPT-6 AstraOpenAI | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs | Gemini 3.1 ProGoogle DeepMind | family variantstext |
 DeepSeek-V4.1-FlashDeepSeek | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs | Grok 4.6xAI | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs | Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini 3 Flash vs Mistral Medium 3.5 128B FAQs
Is Gemini 3 Flash or Mistral Medium 3.5 128B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3 Flash and Mistral Medium 3.5 128B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3 Flash or Mistral Medium 3.5 128B?+
Only Gemini 3 Flash has a directly sourced input price: $0.50 per million tokens. Only Gemini 3 Flash has a directly sourced output price: $3.00 per million tokens.
Which has a larger context window, Gemini 3 Flash or Mistral Medium 3.5 128B?+
Gemini 3 Flash has the larger sourced context window. Gemini 3 Flash supports 1,049K and Mistral Medium 3.5 128B supports 262K.
Which performs better in benchmarks, Gemini 3 Flash or Mistral Medium 3.5 128B?+
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 Mistral Medium 3.5 128B be self-hosted?+
Mistral Medium 3.5 128B is the only model in this pair currently marked as self-hostable. Gemini 3 Flash is not marked open weight; Mistral Medium 3.5 128B is open weight.
Can Gemini 3 Flash and Mistral Medium 3.5 128B understand images?+
Gemini 3 Flash is documented with image input; Mistral Medium 3.5 128B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 3 Flash or Mistral Medium 3.5 128B?+
Neither has a larger sourced maximum output. Gemini 3 Flash is 66K and Mistral Medium 3.5 128B is —.
Do Gemini 3 Flash and Mistral Medium 3.5 128B support reasoning and tool use?+
Gemini 3 Flash: reasoning, tool calling, and image input. Mistral Medium 3.5 128B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 3 Flash or Mistral Medium 3.5 128B?+
Gemini 3 Flash has 2 sourced provider routes; Mistral Medium 3.5 128B has 0, so Gemini 3 Flash has broader tracked availability.
Which offers better value, Gemini 3 Flash or Mistral Medium 3.5 128B?+
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.