Gemini 3.8 Flash Cyber vs Mistral Medium 3.5 128B

At a Glance

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Gemini 3.8 Flash CyberGoogle DeepMind
Pricing and Limits
Context windowMaximum documented tokensNot reported262K
Model facts checkedSep 2, 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

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

FieldGemini 3.8 Flash CyberMistral-Medium-3.5-128B
DeveloperGoogle DeepMindMistral AI
FamilyGemini 3Mistral Medium 3 5 128b
ModelGemini 3.8 Flash CyberMistral-Medium-3.5-128B
VersionGemini 3.8 Flash CyberMistral-Medium-3.5-128B
Lifecycleactiveactive
Released2026-09-02Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context windowUnknown262K
Total parametersUnknown127.7B
Active parametersUnknownUnknown
LicenseUnknownother
Open weightsNoYes
API availableNoUnknown
Self-hostableNoYes
Provider accessUnknownUnknown
Capabilitiesautomated-patching, cybersecurity, reasoning, vulnerability-detectionchat, generation, reasoning, tools

Gemini 3.8 Flash Cyber Capabilities

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

Mistral Medium 3.5 128B Capabilities

chatgenerationreasoningtools
Serving providers0
Canonical IDmistralai/Mistral-Medium-3.5-128B

Primary Evidence

Sources and Freshness

Questions

Gemini 3.8 Flash Cyber vs Mistral Medium 3.5 128B FAQs

Is Gemini 3.8 Flash Cyber or Mistral Medium 3.5 128B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.8 Flash Cyber 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 3.8 Flash Cyber or Mistral Medium 3.5 128B?+

Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.

Which has a larger context window, Gemini 3.8 Flash Cyber or Mistral Medium 3.5 128B?+

Neither model has a larger sourced context window in this comparison. Gemini 3.8 Flash Cyber is — and Mistral Medium 3.5 128B is 262K.

Which performs better in benchmarks, Gemini 3.8 Flash Cyber or Mistral Medium 3.5 128B?+

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

Can Gemini 3.8 Flash Cyber 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 3.8 Flash Cyber is not marked open weight; Mistral Medium 3.5 128B is open weight.

Can Gemini 3.8 Flash Cyber and Mistral Medium 3.5 128B understand images?+

Gemini 3.8 Flash Cyber is not 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 3.8 Flash Cyber or Mistral Medium 3.5 128B?+

Neither has a larger sourced maximum output. Gemini 3.8 Flash Cyber is — and Mistral Medium 3.5 128B is —.

Do Gemini 3.8 Flash Cyber and Mistral Medium 3.5 128B support reasoning and tool use?+

Gemini 3.8 Flash Cyber: reasoning. 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 3.8 Flash Cyber or Mistral Medium 3.5 128B?+

Gemini 3.8 Flash Cyber has 0 sourced provider routes; Mistral Medium 3.5 128B has 0, a tie.

Which offers better value, Gemini 3.8 Flash Cyber 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.

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