DeepSeek V4.1 Flash vs Gemini 3.5 Flash
At a Glance
| Compare |  DeepSeek V4.1 FlashDeepSeek |  Gemini 3.5 FlashGoogle DeepMind |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #15 of 4672.1 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | #5 of 44$0.022 per LiveBench case | #25 of 44$0.140 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #15 of 3856.8 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.15DeepSeek ↗ · Sep 10, 2026 | $1.50Google AI ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $0.60Deepinfra ↗ · Sep 21, 2026 | $9.00Google AI ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,049K |
| Model facts checked | Sep 10, 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 | DeepSeek-V4.1-Flash | Gemini 3.5 Flash |
|---|---|---|
| LiveBench2026-06-25 · overall · leader | 83.20100% of row best · percent · deepseek-v4.1-flash-max · 36,355 output tokens / case | 78.8495% of row best · percent · gemini-3.5-flash-high · 15,522 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 88.03100% of row best · points · DeepSeek V4.1 Flash (max) · 18,199 output tokens / case | 75.5886% of row best · points · Gemini 3.5 Flash (high thinking) · 16,743 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winNo 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 | DeepSeek-V4.1-Flash | Gemini 3.5 Flash |
|---|---|---|
| Developer | DeepSeek | Google DeepMind |
| Family | Deepseek V4 1 | Gemini 3 |
| Model | DeepSeek-V4.1-Flash | Gemini 3.5 Flash |
| Version | DeepSeek-V4.1-Flash | Gemini 3.5 Flash |
| Lifecycle | active | active |
| Released | 2026-09-10 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Video, Audio, Document |
| Output modalities | Text | Text |
| Context window | 1,049K | 1,049K |
| Total parameters | 763.2B | Unknown |
| Active parameters | Unknown | Unknown |
| License | mit | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | DeepSeek (Standard), Deepinfra (Standard), Together Ai (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | agents, chat, fim, generation, reasoning, responses, structured_outputs, tools, vision | chat, generation, reasoning, tools |
| Architecture design | Causal Encoder-Decoder (20 encoder + 20 decoder layers) | Unknown |
| Backbone parameters | 552000000000 parameters | Unknown |
| Active parameters during decode | 16000000000 parameters | Unknown |
| Active parameters during prefill | 8000000000 parameters | Unknown |
| Pre-training corpus | 45000000000000 tokens | Unknown |
| Reasoning effort range | 1–100 | Unknown |
| Routed experts per MoE layer | 384 experts | Unknown |
| Routed experts per token | 6 experts | Unknown |
| Transformer layers | 40 layers | Unknown |
DeepSeek V4.1 Flash Capabilities
Gemini 3.5 Flash Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
DeepSeek-V4-FlashDeepSeek | vs | DeepSeek-V4.1-FlashDeepSeek | family variantstext |
DeepSeek-V4.1-FlashDeepSeek | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs | DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs | Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
DeepSeek-V4.1-FlashDeepSeek | vs | Grok 4.6xAI | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  GLM-5.3Z.ai | cross-developer peerstext |
DeepSeek-V4.1-FlashDeepSeek | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
DeepSeek V4.1 Flash vs Gemini 3.5 Flash FAQs
Is DeepSeek V4.1 Flash or Gemini 3.5 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4.1 Flash and Gemini 3.5 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek V4.1 Flash or Gemini 3.5 Flash?+
DeepSeek V4.1 Flash is $0.15 and Gemini 3.5 Flash is $1.50 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric. DeepSeek V4.1 Flash is $0.60 and Gemini 3.5 Flash is $9.00 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric.
Which has a larger context window, DeepSeek V4.1 Flash or Gemini 3.5 Flash?+
Neither model has a larger sourced context window in this comparison. DeepSeek V4.1 Flash is 1,049K and Gemini 3.5 Flash is 1,049K.
Which performs better in benchmarks, DeepSeek V4.1 Flash or Gemini 3.5 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can DeepSeek V4.1 Flash or Gemini 3.5 Flash be self-hosted?+
DeepSeek V4.1 Flash is the only model in this pair currently marked as self-hostable. DeepSeek V4.1 Flash is open weight; Gemini 3.5 Flash is not marked open weight.
Can DeepSeek V4.1 Flash and Gemini 3.5 Flash understand images?+
DeepSeek V4.1 Flash is documented with image input; Gemini 3.5 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek V4.1 Flash or Gemini 3.5 Flash?+
DeepSeek V4.1 Flash has the larger sourced maximum output: DeepSeek V4.1 Flash supports 393K and Gemini 3.5 Flash supports 66K output tokens.
Do DeepSeek V4.1 Flash and Gemini 3.5 Flash support reasoning and tool use?+
DeepSeek V4.1 Flash: reasoning, tool calling, and image input. Gemini 3.5 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V4.1 Flash or Gemini 3.5 Flash?+
DeepSeek V4.1 Flash has 3 sourced provider routes; Gemini 3.5 Flash has 2, so DeepSeek V4.1 Flash has broader tracked availability.
Which offers better value, DeepSeek V4.1 Flash or Gemini 3.5 Flash?+
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.