Bolmo 7B vs Llama 4 Scout 17B 16E Instruct

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.10Deepinfra · Sep 21, 2026
Output priceFrom · USD / 1M tokensNot reported$0.30Deepinfra · Sep 21, 2026
Context windowMaximum documented tokens66K10,000K
Model facts checkedSep 3, 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

FieldBolmo 7BLlama-4-Scout-17B-16E-Instruct
DeveloperAi2Meta
FamilyBolmoLlama 4 Scout 17b 16e Instruct
ModelBolmo 7BLlama-4-Scout-17B-16E-Instruct
VersionBolmo 7BLlama-4-Scout-17B-16E-Instruct
Lifecycleactiveactive
Released2025-12-132025-04-05
Knowledge cutoff2024-12-01Unknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window66K10,000K
Total parameters7.6B108.6B
Active parametersUnknown17B
Licenseapache-2.0other
Open weightsYesYes
API availableNoYes
Self-hostableYesYes
Provider accessUnknownDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitiesgenerationchat, generation, tools

Bolmo 7B Capabilities

generation
Serving providers0
Canonical IDallenai/Bolmo-7B

Llama 4 Scout 17B 16E Instruct Capabilities

chatgenerationtools
Serving providers4
Canonical IDmeta-llama/Llama-4-Scout-17B-16E-Instruct

Primary Evidence

Sources and Freshness

Questions

Bolmo 7B vs Llama 4 Scout 17B 16E Instruct FAQs

Is Bolmo 7B or Llama 4 Scout 17B 16E Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Bolmo 7B and Llama 4 Scout 17B 16E Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Bolmo 7B or Llama 4 Scout 17B 16E Instruct?+

Only Llama 4 Scout 17B 16E Instruct has a directly sourced input price: $0.10 per million tokens. Only Llama 4 Scout 17B 16E Instruct has a directly sourced output price: $0.30 per million tokens.

Which has a larger context window, Bolmo 7B or Llama 4 Scout 17B 16E Instruct?+

Llama 4 Scout 17B 16E Instruct has the larger sourced context window. Bolmo 7B supports 66K and Llama 4 Scout 17B 16E Instruct supports 10,000K.

Which performs better in benchmarks, Bolmo 7B or Llama 4 Scout 17B 16E Instruct?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Bolmo 7B or Llama 4 Scout 17B 16E Instruct be self-hosted?+

Both models have the same recorded self-hosting status: supported. Bolmo 7B is open weight; Llama 4 Scout 17B 16E Instruct is open weight.

Can Bolmo 7B and Llama 4 Scout 17B 16E Instruct understand images?+

Bolmo 7B is not documented with image input; Llama 4 Scout 17B 16E Instruct is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Bolmo 7B or Llama 4 Scout 17B 16E Instruct?+

Neither has a larger sourced maximum output. Bolmo 7B is — and Llama 4 Scout 17B 16E Instruct is —.

Do Bolmo 7B and Llama 4 Scout 17B 16E Instruct support reasoning and tool use?+

Bolmo 7B: none of these features are definitively sourced. Llama 4 Scout 17B 16E Instruct: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Bolmo 7B or Llama 4 Scout 17B 16E Instruct?+

Bolmo 7B has 0 sourced provider routes; Llama 4 Scout 17B 16E Instruct has 4, so Llama 4 Scout 17B 16E Instruct has broader tracked availability.

Which offers better value, Bolmo 7B or Llama 4 Scout 17B 16E 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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