DeepSeek V4 Flash vs Gemini 3.8 Flash

At a Glance

Compare
Gemini 3.8 FlashGoogle DeepMind
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#8 of 4682.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 54.7–88.0
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#26 of 44$0.160 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#8 of 3860.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.7–63.4
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.0868Openrouter · Aug 28, 2026$0.75Google AI · Sep 2, 2026
Output priceFrom · USD / 1M tokens$0.1736Openrouter · Aug 28, 2026$3.75Google AI · Sep 2, 2026
Context windowMaximum documented tokens1,049K1,049K
Model facts checkedAug 28, 2026View model evidence →Sep 2, 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

All benchmark results →
BenchmarkDeepSeek-V4-FlashGemini 3.8 Flash
LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader1.8097% of row best · score · Deepseek V4 Flash (High) (20260731); 95% CI [1.06225523, 2.53222539]; sessions 64482; observations 6405377; rank 224.71100% of row best · score · Gemini 3.8 Flash (High); 95% CI [2.80246501, 6.61533867]; sessions 12534; observations 712246; rank 13
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,431.7996% of row best · rating · deepseek-v4-flash; 95% CI [1427.66110387, 1435.91557810]; votes 48887; rank 831,494.67100% of row best · rating · gemini-3.8-flash-high; 95% CI [1486.13928353, 1503.20869643]; votes 5076; rank 6
LiveBench2026-06-25 · overall · leader69.6786% of row best · percent · deepseek-v4-flash · 34,434 output tokens / case80.85100% of row best · percent · gemini-3.8-flash-high · 42,786 output tokens / case
ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified78.00100% of row best · points · DeepSeek V4 Flash (xhigh) · 12,709 output tokens / case77.82100% of row best · points · Gemini 3.8 Flash (high thinking) · 13,616 output tokens / case
Overall ResultCounted from the protocol-matched rows above0 benchmark wins3 benchmark winsOverall lead

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

FieldDeepSeek-V4-FlashGemini 3.8 Flash
DeveloperDeepSeekGoogle DeepMind
FamilyDeepseek V4 FlashGemini 3
ModelDeepSeek-V4-FlashGemini 3.8 Flash
VersionDeepSeek-V4-FlashGemini 3.8 Flash
Lifecycleretiredactive
Released2026-04-242026-09-02
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Video, Audio, Document
Output modalitiesTextText
Context window1,049K1,049K
Total parameters290.9BUnknown
Active parameters13BUnknown
LicensemitUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepSeek (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitieschat, generation, reasoningchat, code_execution, computer_use, generation, reasoning, structured_outputs, tools

DeepSeek V4 Flash Capabilities

chatgenerationreasoning
Serving providers5
Canonical IDdeepseek-ai/DeepSeek-V4-Flash

Gemini 3.8 Flash Capabilities

chatcode executioncomputer usegenerationreasoningstructured outputstools
Serving providers2
Canonical IDgoogle-deepmind/gemini-3.8-flash

Primary Evidence

Sources and Freshness

Questions

DeepSeek V4 Flash vs Gemini 3.8 Flash FAQs

Is DeepSeek V4 Flash or Gemini 3.8 Flash better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4 Flash and Gemini 3.8 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, DeepSeek V4 Flash or Gemini 3.8 Flash?+

DeepSeek V4 Flash is $0.0868 and Gemini 3.8 Flash is $0.75 per million tokens, so DeepSeek V4 Flash is cheaper on this metric. DeepSeek V4 Flash is $0.1736 and Gemini 3.8 Flash is $3.75 per million tokens, so DeepSeek V4 Flash is cheaper on this metric.

Which has a larger context window, DeepSeek V4 Flash or Gemini 3.8 Flash?+

Neither model has a larger sourced context window in this comparison. DeepSeek V4 Flash is 1,049K and Gemini 3.8 Flash is 1,049K.

Which performs better in benchmarks, DeepSeek V4 Flash or Gemini 3.8 Flash?+

Gemini 3.8 Flash leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.

Can DeepSeek V4 Flash or Gemini 3.8 Flash be self-hosted?+

DeepSeek V4 Flash is the only model in this pair currently marked as self-hostable. DeepSeek V4 Flash is open weight; Gemini 3.8 Flash is not marked open weight.

Can DeepSeek V4 Flash and Gemini 3.8 Flash understand images?+

DeepSeek V4 Flash is not documented with image input; Gemini 3.8 Flash is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V4 Flash or Gemini 3.8 Flash?+

Neither has a larger sourced maximum output. DeepSeek V4 Flash is — and Gemini 3.8 Flash is 66K.

Do DeepSeek V4 Flash and Gemini 3.8 Flash support reasoning and tool use?+

DeepSeek V4 Flash: reasoning. Gemini 3.8 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V4 Flash or Gemini 3.8 Flash?+

DeepSeek V4 Flash has 5 sourced provider routes; Gemini 3.8 Flash has 2, so DeepSeek V4 Flash has broader tracked availability.

Which offers better value, DeepSeek V4 Flash or Gemini 3.8 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.

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