Granite 4.2 30B vs Llama 3.1 405B Instruct

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokens$0.16Deepinfra · Sep 23, 2026Not reported
Output priceFrom · USD / 1M tokens$0.65Deepinfra · Sep 23, 2026Not reported
Context windowMaximum documented tokens131K131K
Model facts checkedSep 2, 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

FieldGranite 4.2 30BLlama-3.1-405B-Instruct
DeveloperIBMMeta
FamilyGranite 4 2Llama 3 1 405b Instruct
ModelGranite 4.2 30BLlama-3.1-405B-Instruct
VersionGranite 4.2 30BLlama-3.1-405B-Instruct
Lifecycleactiveactive
Released2026-08-252024-07-23
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window131K131K
Total parameters29.3B405.9B
Active parametersUnknownUnknown
Licenseapache-2.0llama3.1
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessDeepinfra (Standard)Together Ai (Standard)
Capabilitieschat, generation, reasoning, structured_outputs, toolschat, generation, tools

Granite 4.2 30B Capabilities

chatgenerationreasoningstructured outputstools
Serving providers1
Canonical IDibm-granite/granite-4.2-30b

Llama 3.1 405B Instruct Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Granite 4.2 30B vs Llama 3.1 405B Instruct FAQs

Is Granite 4.2 30B or Llama 3.1 405B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Granite 4.2 30B 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, Granite 4.2 30B or Llama 3.1 405B Instruct?+

Only Granite 4.2 30B has a directly sourced input price: $0.16 per million tokens. Only Granite 4.2 30B has a directly sourced output price: $0.65 per million tokens.

Which has a larger context window, Granite 4.2 30B or Llama 3.1 405B Instruct?+

Neither model has a larger sourced context window in this comparison. Granite 4.2 30B is 131K and Llama 3.1 405B Instruct is 131K.

Which performs better in benchmarks, Granite 4.2 30B 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 Granite 4.2 30B or Llama 3.1 405B Instruct be self-hosted?+

Both models have the same recorded self-hosting status: supported. Granite 4.2 30B is open weight; Llama 3.1 405B Instruct is open weight.

Can Granite 4.2 30B and Llama 3.1 405B Instruct understand images?+

Granite 4.2 30B is not 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, Granite 4.2 30B or Llama 3.1 405B Instruct?+

Neither has a larger sourced maximum output. Granite 4.2 30B is — and Llama 3.1 405B Instruct is —.

Do Granite 4.2 30B and Llama 3.1 405B Instruct support reasoning and tool use?+

Granite 4.2 30B: reasoning and tool calling. Llama 3.1 405B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Granite 4.2 30B or Llama 3.1 405B Instruct?+

Granite 4.2 30B has 1 sourced provider route; Llama 3.1 405B Instruct has 1, a tie.

Which offers better value, Granite 4.2 30B 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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