Qwen3 Coder Next vs Gemini 3.8 Flash Cyber

At a Glance

Compare
Gemini 3.8 Flash CyberGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.12Openrouter · Sep 22, 2026Not reported
Output priceFrom · USD / 1M tokens$0.80Openrouter · Sep 22, 2026Not reported
Context windowMaximum documented tokens262KNot 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

FieldQwen3-Coder-NextGemini 3.8 Flash Cyber
DeveloperQwenGoogle DeepMind
FamilyQwen3 Coder NextGemini 3
ModelQwen3-Coder-NextGemini 3.8 Flash Cyber
VersionQwen3-Coder-NextGemini 3.8 Flash Cyber
Lifecycleactiveactive
Released2026-02-022026-09-02
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window262KUnknown
Total parameters79.7BUnknown
Active parameters3BUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableYesNo
Self-hostableYesNo
Provider accessHugging Face (Standard), Openrouter (Standard)Unknown
Capabilitieschat, generation, toolsautomated-patching, cybersecurity, reasoning, vulnerability-detection

Qwen3 Coder Next Capabilities

chatgenerationtools
Serving providers2
Canonical IDQwen/Qwen3-Coder-Next

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

Qwen3 Coder Next vs Gemini 3.8 Flash Cyber FAQs

Is Qwen3 Coder Next or Gemini 3.8 Flash Cyber better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3 Coder Next 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, Qwen3 Coder Next or Gemini 3.8 Flash Cyber?+

Only Qwen3 Coder Next has a directly sourced input price: $0.12 per million tokens. Only Qwen3 Coder Next has a directly sourced output price: $0.80 per million tokens.

Which has a larger context window, Qwen3 Coder Next or Gemini 3.8 Flash Cyber?+

Neither model has a larger sourced context window in this comparison. Qwen3 Coder Next is 262K and Gemini 3.8 Flash Cyber is —.

Which performs better in benchmarks, Qwen3 Coder Next 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 Qwen3 Coder Next or Gemini 3.8 Flash Cyber be self-hosted?+

Qwen3 Coder Next is the only model in this pair currently marked as self-hostable. Qwen3 Coder Next is open weight; Gemini 3.8 Flash Cyber is not marked open weight.

Can Qwen3 Coder Next and Gemini 3.8 Flash Cyber understand images?+

Qwen3 Coder Next 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, Qwen3 Coder Next or Gemini 3.8 Flash Cyber?+

Neither has a larger sourced maximum output. Qwen3 Coder Next is — and Gemini 3.8 Flash Cyber is —.

Do Qwen3 Coder Next and Gemini 3.8 Flash Cyber support reasoning and tool use?+

Qwen3 Coder Next: tool calling. Gemini 3.8 Flash Cyber: reasoning. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3 Coder Next or Gemini 3.8 Flash Cyber?+

Qwen3 Coder Next has 2 sourced provider routes; Gemini 3.8 Flash Cyber has 0, so Qwen3 Coder Next has broader tracked availability.

Which offers better value, Qwen3 Coder Next 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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