Command A Translate vs Llama 4 Maverick 17B 128E

At a Glance

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Pricing and Limits
Context windowMaximum documented tokens8K1,000K
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

FieldCommand A TranslateLlama-4-Maverick-17B-128E
DeveloperCohereMeta
FamilyCommand ALlama 4 Maverick 17b 128e
ModelCommand A TranslateLlama-4-Maverick-17B-128E
VersionCommand A TranslateLlama-4-Maverick-17B-128E
Lifecycleactiveactive
Released2025-08-282025-04-05
Knowledge cutoff2024-06-01Unknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window8K1,000K
Total parameters111B401.6B
Active parametersUnknown17B
LicenseUnknownother
Open weightsNoYes
API availableYesUnknown
Self-hostableNoYes
Provider accessCohere (Standard)Unknown
Capabilitieschat, generation, structured_outputs, translationchat, generation, tools

Command A Translate Capabilities

chatgenerationstructured outputstranslation
Serving providers1
Canonical IDcoherelabs/command-a-translate-08-2025

Llama 4 Maverick 17B 128E Capabilities

chatgenerationtools
Serving providers0
Canonical IDmeta-llama/Llama-4-Maverick-17B-128E

Primary Evidence

Sources and Freshness

Questions

Command A Translate vs Llama 4 Maverick 17B 128E FAQs

Is Command A Translate or Llama 4 Maverick 17B 128E better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Command A Translate and Llama 4 Maverick 17B 128E, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Command A Translate or Llama 4 Maverick 17B 128E?+

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, Command A Translate or Llama 4 Maverick 17B 128E?+

Llama 4 Maverick 17B 128E has the larger sourced context window. Command A Translate supports 8K and Llama 4 Maverick 17B 128E supports 1,000K.

Which performs better in benchmarks, Command A Translate or Llama 4 Maverick 17B 128E?+

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

Can Command A Translate or Llama 4 Maverick 17B 128E be self-hosted?+

Llama 4 Maverick 17B 128E is the only model in this pair currently marked as self-hostable. Command A Translate is not marked open weight; Llama 4 Maverick 17B 128E is open weight.

Can Command A Translate and Llama 4 Maverick 17B 128E understand images?+

Command A Translate is not documented with image input; Llama 4 Maverick 17B 128E is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Command A Translate or Llama 4 Maverick 17B 128E?+

Neither has a larger sourced maximum output. Command A Translate is 8K and Llama 4 Maverick 17B 128E is —.

Do Command A Translate and Llama 4 Maverick 17B 128E support reasoning and tool use?+

Command A Translate: none of these features are definitively sourced. Llama 4 Maverick 17B 128E: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Command A Translate or Llama 4 Maverick 17B 128E?+

Command A Translate has 1 sourced provider route; Llama 4 Maverick 17B 128E has 0, so Command A Translate has broader tracked availability.

Which offers better value, Command A Translate or Llama 4 Maverick 17B 128E?+

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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