FLUX.2 klein 4B FP8 vs Llama 3.1 8B Instruct

At a Glance

Compare
FLUX.2 klein 4B FP8Black Forest Labs
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.050Openrouter · Sep 23, 2026
Output priceFrom · USD / 1M tokensNot reported$0.080Openrouter · Sep 23, 2026
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-4b-fp8Llama-3.1-8B-Instruct
DeveloperBlack Forest LabsMeta
FamilyFlux 2 Klein 4b Fp8Llama 3 1 8b Instruct
ModelFLUX.2-klein-4b-fp8Llama-3.1-8B-Instruct
VersionFLUX.2-klein-4b-fp8Llama-3.1-8B-Instruct
Lifecycleactiveactive
Released2026-01-152024-07-23
Knowledge cutoffUnknownUnknown
Input modalitiesImageText
Output modalitiesImageText
Context windowUnknown131K
Total parameters4B8B
Active parametersUnknownUnknown
Licenseapache-2.0llama3.1
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownHugging Face (Standard), Openrouter (Standard)
Capabilitiesgenerationchat, generation, tools

FLUX.2 klein 4B FP8 Capabilities

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

Llama 3.1 8B Instruct Capabilities

chatgenerationtools
Serving providers2
Canonical IDmeta-llama/Llama-3.1-8B-Instruct

Primary Evidence

Sources and Freshness

Questions

FLUX.2 klein 4B FP8 vs Llama 3.1 8B Instruct FAQs

Is FLUX.2 klein 4B FP8 or Llama 3.1 8B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both FLUX.2 klein 4B FP8 and Llama 3.1 8B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, FLUX.2 klein 4B FP8 or Llama 3.1 8B Instruct?+

Only Llama 3.1 8B Instruct has a directly sourced input price: $0.050 per million tokens. Only Llama 3.1 8B Instruct has a directly sourced output price: $0.080 per million tokens.

Which has a larger context window, FLUX.2 klein 4B FP8 or Llama 3.1 8B Instruct?+

Neither model has a larger sourced context window in this comparison. FLUX.2 klein 4B FP8 is — and Llama 3.1 8B Instruct is 131K.

Which performs better in benchmarks, FLUX.2 klein 4B FP8 or Llama 3.1 8B 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 4B FP8 or Llama 3.1 8B Instruct be self-hosted?+

Both models have the same recorded self-hosting status: supported. FLUX.2 klein 4B FP8 is open weight; Llama 3.1 8B Instruct is open weight.

Can FLUX.2 klein 4B FP8 and Llama 3.1 8B Instruct understand images?+

FLUX.2 klein 4B FP8 is documented with image input; Llama 3.1 8B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, FLUX.2 klein 4B FP8 or Llama 3.1 8B Instruct?+

Neither has a larger sourced maximum output. FLUX.2 klein 4B FP8 is — and Llama 3.1 8B Instruct is —.

Do FLUX.2 klein 4B FP8 and Llama 3.1 8B Instruct support reasoning and tool use?+

FLUX.2 klein 4B FP8: image input. Llama 3.1 8B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, FLUX.2 klein 4B FP8 or Llama 3.1 8B Instruct?+

FLUX.2 klein 4B FP8 has 0 sourced provider routes; Llama 3.1 8B Instruct has 2, so Llama 3.1 8B Instruct has broader tracked availability.

Which offers better value, FLUX.2 klein 4B FP8 or Llama 3.1 8B 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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