Llama 3.1 405B vs NVIDIA Nemotron 3.5 Lightning 30B A3B

At a Glance

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Pricing and Limits
Context windowMaximum documented tokens131K1,049K
Model facts checkedAug 28, 2026View model evidence →Sep 3, 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-3.1-405BNVIDIA Nemotron 3.5 Lightning 30B-A3B
DeveloperMetaNVIDIA
FamilyLlama 3 1 405bNvidia Nemotron 3 5 Lightning
ModelLlama-3.1-405BNVIDIA Nemotron 3.5 Lightning 30B-A3B
VersionLlama-3.1-405BNVIDIA Nemotron 3.5 Lightning 30B-A3B
Lifecycleactiveactive
Released2024-07-232026-08-11
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window131K1,049K
Total parameters405.9B30B
Active parametersUnknown3B
Licensellama3.1openmdw-1.1
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessTogether Ai (Standard)Fireworks Ai (Standard)
Capabilitiesgenerationagents, chat, generation, reasoning, tools

Llama 3.1 405B Capabilities

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

NVIDIA Nemotron 3.5 Lightning 30B A3B Capabilities

agentschatgenerationreasoningtools
Serving providers1
Canonical IDnvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Primary Evidence

Sources and Freshness

Questions

Llama 3.1 405B vs NVIDIA Nemotron 3.5 Lightning 30B A3B FAQs

Is Llama 3.1 405B or NVIDIA Nemotron 3.5 Lightning 30B A3B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.1 405B and NVIDIA Nemotron 3.5 Lightning 30B A3B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 3.1 405B or NVIDIA Nemotron 3.5 Lightning 30B A3B?+

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, Llama 3.1 405B or NVIDIA Nemotron 3.5 Lightning 30B A3B?+

NVIDIA Nemotron 3.5 Lightning 30B A3B has the larger sourced context window. Llama 3.1 405B supports 131K and NVIDIA Nemotron 3.5 Lightning 30B A3B supports 1,049K.

Which performs better in benchmarks, Llama 3.1 405B or NVIDIA Nemotron 3.5 Lightning 30B A3B?+

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 NVIDIA Nemotron 3.5 Lightning 30B A3B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Llama 3.1 405B is open weight; NVIDIA Nemotron 3.5 Lightning 30B A3B is open weight.

Can Llama 3.1 405B and NVIDIA Nemotron 3.5 Lightning 30B A3B understand images?+

Llama 3.1 405B is not documented with image input; NVIDIA Nemotron 3.5 Lightning 30B A3B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Llama 3.1 405B or NVIDIA Nemotron 3.5 Lightning 30B A3B?+

Neither has a larger sourced maximum output. Llama 3.1 405B is — and NVIDIA Nemotron 3.5 Lightning 30B A3B is —.

Do Llama 3.1 405B and NVIDIA Nemotron 3.5 Lightning 30B A3B support reasoning and tool use?+

Llama 3.1 405B: none of these features are definitively sourced. NVIDIA Nemotron 3.5 Lightning 30B A3B: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 3.1 405B or NVIDIA Nemotron 3.5 Lightning 30B A3B?+

Llama 3.1 405B has 1 sourced provider route; NVIDIA Nemotron 3.5 Lightning 30B A3B has 1, a tie.

Which offers better value, Llama 3.1 405B or NVIDIA Nemotron 3.5 Lightning 30B A3B?+

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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