Llama 3.1 405B Instruct vs Llama 3.3 70B Instruct

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.10Openrouter ↗ · Oct 19, 2026
Output priceFrom · USD / 1M tokensNot reported$0.32Openrouter ↗ · Oct 19, 2026
Context windowMaximum documented tokens131K131K
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 →

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-3.1-405B-InstructLlama-3.3-70B-Instruct
DeveloperMetaMeta
FamilyLlama 3 1 405b InstructLlama 3 3 70b Instruct
ModelLlama-3.1-405B-InstructLlama-3.3-70B-Instruct
VersionLlama-3.1-405B-InstructLlama-3.3-70B-Instruct
Lifecycleactiveactive
Released2024-07-232024-12-06
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window131K131K
Total parameters405.9B70.6B
Active parametersUnknownUnknown
Licensellama3.1llama3.3
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessTogether Ai (Standard)Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitieschat, generation, toolschat, generation, tools

Llama 3.1 405B Instruct Capabilities

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

Llama 3.3 70B Instruct Capabilities

chatgenerationtools
Serving providers3
Canonical IDmeta-llama/Llama-3.3-70B-Instruct

Primary Evidence

Sources and Freshness

Questions

Llama 3.1 405B Instruct vs Llama 3.3 70B Instruct FAQs

Is Llama 3.1 405B Instruct or Llama 3.3 70B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.1 405B Instruct and Llama 3.3 70B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 3.1 405B Instruct or Llama 3.3 70B Instruct?+

Only Llama 3.3 70B Instruct has a directly sourced input price: $0.10 per million tokens. Only Llama 3.3 70B Instruct has a directly sourced output price: $0.32 per million tokens.

Which has a larger context window, Llama 3.1 405B Instruct or Llama 3.3 70B Instruct?+

Both models have the same sourced context window: 131,072 tokens each.

Which performs better in benchmarks, Llama 3.1 405B Instruct or Llama 3.3 70B Instruct?+

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 Instruct or Llama 3.3 70B Instruct be self-hosted?+

Both models have the same sourced self-hosting status: supported. Llama 3.1 405B Instruct is open weight; Llama 3.3 70B Instruct is open weight.

Can Llama 3.1 405B Instruct and Llama 3.3 70B Instruct understand images?+

Llama 3.1 405B Instruct is not documented with image input; Llama 3.3 70B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Llama 3.1 405B Instruct or Llama 3.3 70B Instruct?+

Neither model has a sourced maximum output in this comparison, so a larger limit cannot be determined.

Do Llama 3.1 405B Instruct and Llama 3.3 70B Instruct support reasoning and tool use?+

Llama 3.1 405B Instruct: tool calling. Llama 3.3 70B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 3.1 405B Instruct or Llama 3.3 70B Instruct?+

Llama 3.1 405B Instruct has 1 sourced provider route; Llama 3.3 70B Instruct has 3, so Llama 3.3 70B Instruct has broader tracked availability.

Which offers better value, Llama 3.1 405B Instruct or Llama 3.3 70B 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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