Llama 3.1 405B vs Qwen3.8 Flash

At a Glance

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Intelligence, Cost, and Efficiency
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#4 of 44$0.021 per LiveBench case
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.113Deepinfra · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$0.382Deepinfra · Sep 22, 2026
Context windowMaximum documented tokens131K1,000K
Model facts checkedAug 28, 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

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

FieldLlama-3.1-405BQwen3.8-Flash
DeveloperMetaQwen
FamilyLlama 3 1 405bQwen3 8 Flash
ModelLlama-3.1-405BQwen3.8-Flash
VersionLlama-3.1-405BQwen3.8-Flash
Lifecycleactiveactive
Released2024-07-23Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Video
Output modalitiesTextText
Context window131K1,000K
Total parameters405.9BUnknown
Active parametersUnknownUnknown
Licensellama3.1Unknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessTogether Ai (Standard)Alibaba Cloud Model Studio (Standard), Deepinfra (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitiesgenerationagents, chat, computer-use, reasoning, structured_outputs, tools, vision

Llama 3.1 405B Capabilities

generation
Serving providers1
Canonical IDmeta-llama/Llama-3.1-405B

Qwen3.8 Flash Capabilities

agentschatcomputer-usereasoningstructured outputstoolsvision
Serving providers4
Canonical IDqwen/qwen3.8-flash

Primary Evidence

Sources and Freshness

Questions

Llama 3.1 405B vs Qwen3.8 Flash FAQs

Is Llama 3.1 405B or Qwen3.8 Flash better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.1 405B and Qwen3.8 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 3.1 405B or Qwen3.8 Flash?+

Only Qwen3.8 Flash has a directly sourced input price: $0.113 per million tokens. Only Qwen3.8 Flash has a directly sourced output price: $0.382 per million tokens.

Which has a larger context window, Llama 3.1 405B or Qwen3.8 Flash?+

Qwen3.8 Flash has the larger sourced context window. Llama 3.1 405B supports 131K and Qwen3.8 Flash supports 1,000K.

Which performs better in benchmarks, Llama 3.1 405B or Qwen3.8 Flash?+

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

Can Llama 3.1 405B or Qwen3.8 Flash be self-hosted?+

Llama 3.1 405B is the only model in this pair currently marked as self-hostable. Llama 3.1 405B is open weight; Qwen3.8 Flash is not marked open weight.

Can Llama 3.1 405B and Qwen3.8 Flash understand images?+

Llama 3.1 405B is not documented with image input; Qwen3.8 Flash is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Llama 3.1 405B or Qwen3.8 Flash?+

Neither has a larger sourced maximum output. Llama 3.1 405B is — and Qwen3.8 Flash is 131K.

Do Llama 3.1 405B and Qwen3.8 Flash support reasoning and tool use?+

Llama 3.1 405B: none of these features are definitively sourced. Qwen3.8 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 3.1 405B or Qwen3.8 Flash?+

Llama 3.1 405B has 1 sourced provider route; Qwen3.8 Flash has 4, so Qwen3.8 Flash has broader tracked availability.

Which offers better value, Llama 3.1 405B or Qwen3.8 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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