FLUX.2 klein Base 4B FP8 vs Llama 3.1 405B Instruct

At a Glance

Compare
FLUX.2 klein Base 4B FP8Black Forest Labs
Pricing and Limits
Context windowMaximum documented tokensNot reported131K
Model facts checkedAug 28, 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 →

Different Model RolesThese models do not share a sourced market category. Their primary-source facts remain comparable below, while performance claims require matched evidence.

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

FieldFLUX.2-klein-base-4b-fp8Llama-3.1-405B-Instruct
DeveloperBlack Forest LabsMeta
FamilyFlux 2 Klein Base 4b Fp8Llama 3 1 405b Instruct
ModelFLUX.2-klein-base-4b-fp8Llama-3.1-405B-Instruct
VersionFLUX.2-klein-base-4b-fp8Llama-3.1-405B-Instruct
Lifecycleactiveactive
Released2026-01-152024-07-23
Knowledge cutoffUnknownUnknown
Input modalitiesImageText
Output modalitiesImageText
Context windowUnknown131K
Total parameters4B405.9B
Active parametersUnknownUnknown
Licenseapache-2.0llama3.1
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownTogether Ai (Standard)
Capabilitiesgenerationchat, generation, tools

FLUX.2 klein Base 4B FP8 Capabilities

generation
Serving providers0
Canonical IDblack-forest-labs/FLUX.2-klein-base-4b-fp8

Llama 3.1 405B Instruct Capabilities

chatgenerationtools
Serving providers1
Canonical IDmeta-llama/Llama-3.1-405B-Instruct

Primary Evidence

Sources and Freshness

Questions

FLUX.2 klein Base 4B FP8 vs Llama 3.1 405B Instruct FAQs

Is FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both FLUX.2 klein Base 4B FP8 and Llama 3.1 405B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct?+

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, FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct?+

Neither model has a larger sourced context window in this comparison. FLUX.2 klein Base 4B FP8 is — and Llama 3.1 405B Instruct is 131K.

Which performs better in benchmarks, FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct?+

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

Can FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct be self-hosted?+

Both models have the same recorded self-hosting status: supported. FLUX.2 klein Base 4B FP8 is open weight; Llama 3.1 405B Instruct is open weight.

Can FLUX.2 klein Base 4B FP8 and Llama 3.1 405B Instruct understand images?+

FLUX.2 klein Base 4B FP8 is documented with image input; Llama 3.1 405B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct?+

Neither has a larger sourced maximum output. FLUX.2 klein Base 4B FP8 is — and Llama 3.1 405B Instruct is —.

Do FLUX.2 klein Base 4B FP8 and Llama 3.1 405B Instruct support reasoning and tool use?+

FLUX.2 klein Base 4B FP8: image input. Llama 3.1 405B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct?+

FLUX.2 klein Base 4B FP8 has 0 sourced provider routes; Llama 3.1 405B Instruct has 1, so Llama 3.1 405B Instruct has broader tracked availability.

Which offers better value, FLUX.2 klein Base 4B FP8 or Llama 3.1 405B Instruct?+

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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