DeepSeek V3.2 vs Gemini 3.8 Flash Cyber

At a Glance

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Gemini 3.8 Flash CyberGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.26Deepinfra · Sep 22, 2026Not reported
Output priceFrom · USD / 1M tokens$0.38Deepinfra · Sep 22, 2026Not reported
Context windowMaximum documented tokens164KNot reported
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 →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldDeepSeek-V3.2Gemini 3.8 Flash Cyber
DeveloperDeepSeekGoogle DeepMind
FamilyDeepseek V3 2Gemini 3
ModelDeepSeek-V3.2Gemini 3.8 Flash Cyber
VersionDeepSeek-V3.2Gemini 3.8 Flash Cyber
Lifecycleactiveactive
Released2025-12-012026-09-02
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window164KUnknown
Total parameters685.4BUnknown
Active parametersUnknownUnknown
LicensemitUnknown
Open weightsYesNo
API availableYesNo
Self-hostableYesNo
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Unknown
Capabilitieschat, generation, reasoningautomated-patching, cybersecurity, reasoning, vulnerability-detection

DeepSeek V3.2 Capabilities

chatgenerationreasoning
Serving providers3
Canonical IDdeepseek-ai/DeepSeek-V3.2

Gemini 3.8 Flash Cyber Capabilities

automated-patchingcybersecurityreasoningvulnerability-detection
Serving providers0
Canonical IDgoogle-deepmind/gemini-3.8-flash-cyber

Primary Evidence

Sources and Freshness

Questions

DeepSeek V3.2 vs Gemini 3.8 Flash Cyber FAQs

Is DeepSeek V3.2 or Gemini 3.8 Flash Cyber better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V3.2 and Gemini 3.8 Flash Cyber, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, DeepSeek V3.2 or Gemini 3.8 Flash Cyber?+

Only DeepSeek V3.2 has a directly sourced input price: $0.26 per million tokens. Only DeepSeek V3.2 has a directly sourced output price: $0.38 per million tokens.

Which has a larger context window, DeepSeek V3.2 or Gemini 3.8 Flash Cyber?+

Neither model has a larger sourced context window in this comparison. DeepSeek V3.2 is 164K and Gemini 3.8 Flash Cyber is —.

Which performs better in benchmarks, DeepSeek V3.2 or Gemini 3.8 Flash Cyber?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can DeepSeek V3.2 or Gemini 3.8 Flash Cyber be self-hosted?+

DeepSeek V3.2 is the only model in this pair currently marked as self-hostable. DeepSeek V3.2 is open weight; Gemini 3.8 Flash Cyber is not marked open weight.

Can DeepSeek V3.2 and Gemini 3.8 Flash Cyber understand images?+

DeepSeek V3.2 is not documented with image input; Gemini 3.8 Flash Cyber is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V3.2 or Gemini 3.8 Flash Cyber?+

Neither has a larger sourced maximum output. DeepSeek V3.2 is — and Gemini 3.8 Flash Cyber is —.

Do DeepSeek V3.2 and Gemini 3.8 Flash Cyber support reasoning and tool use?+

DeepSeek V3.2: reasoning. Gemini 3.8 Flash Cyber: reasoning. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V3.2 or Gemini 3.8 Flash Cyber?+

DeepSeek V3.2 has 3 sourced provider routes; Gemini 3.8 Flash Cyber has 0, so DeepSeek V3.2 has broader tracked availability.

Which offers better value, DeepSeek V3.2 or Gemini 3.8 Flash Cyber?+

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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