Olmo 3 7B Instruct vs Llama 3.1 8B Instruct

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.050Openrouter ↗ · Oct 19, 2026
Output priceFrom · USD / 1M tokensNot reported$0.080Openrouter ↗ · Oct 19, 2026
Context windowMaximum documented tokens66K131K
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

FieldOlmo-3-7B-InstructLlama-3.1-8B-Instruct
DeveloperAi2Meta
FamilyOlmo 3 7b InstructLlama 3 1 8b Instruct
ModelOlmo-3-7B-InstructLlama-3.1-8B-Instruct
VersionOlmo-3-7B-InstructLlama-3.1-8B-Instruct
Lifecycleactiveactive
ReleasedUnknown2024-07-23
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window66K131K
Total parameters7.3B8B
Active parametersUnknownUnknown
Licenseapache-2.0llama3.1
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownHugging Face (Standard), Openrouter (Standard)
Capabilitieschat, generation, toolschat, generation, tools

Olmo 3 7B Instruct Capabilities

chatgenerationtools
Serving providers0
Canonical IDallenai/Olmo-3-7B-Instruct

Llama 3.1 8B Instruct Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Olmo 3 7B Instruct vs Llama 3.1 8B Instruct FAQs

Is Olmo 3 7B Instruct or Llama 3.1 8B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Olmo 3 7B Instruct 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, Olmo 3 7B Instruct 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, Olmo 3 7B Instruct or Llama 3.1 8B Instruct?+

Llama 3.1 8B Instruct has the larger sourced context window. Olmo 3 7B Instruct supports 65,536 tokens and Llama 3.1 8B Instruct supports 131,072 tokens.

Which performs better in benchmarks, Olmo 3 7B Instruct 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 Olmo 3 7B Instruct or Llama 3.1 8B Instruct be self-hosted?+

Both models have the same sourced self-hosting status: supported. Olmo 3 7B Instruct is open weight; Llama 3.1 8B Instruct is open weight.

Can Olmo 3 7B Instruct and Llama 3.1 8B Instruct understand images?+

Olmo 3 7B Instruct is not 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, Olmo 3 7B Instruct or Llama 3.1 8B Instruct?+

Olmo 3 7B Instruct has a sourced maximum output of 32,768 tokens; Llama 3.1 8B Instruct's maximum output is not reported. A larger limit cannot be determined.

Do Olmo 3 7B Instruct and Llama 3.1 8B Instruct support reasoning and tool use?+

Olmo 3 7B Instruct: tool calling. Llama 3.1 8B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Olmo 3 7B Instruct or Llama 3.1 8B Instruct?+

Olmo 3 7B Instruct 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, Olmo 3 7B Instruct 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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