Llama 4 Maverick 17B 128E Instruct vs o3

Benchmark Performance

Available Benchmarks

No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.
FieldAt a Glance
Meta · activeLlama 4 Maverick 17B 128E InstructVerified Aug 28, 2026
OpenAI · activeo3Verified Sep 3, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldLlama-4-Maverick-17B-128E-Instructo3
DeveloperMetaOpenAI
FamilyLlama 4 Maverick 17b 128e InstructO3
ModelLlama-4-Maverick-17B-128E-Instructo3
VersionLlama-4-Maverick-17B-128E-Instructo3
Lifecycleactiveactive
Released2025-04-052025-04-16
Knowledge cutoffUnknown2024-06-01
Input modalitiesText, ImageText, Image
Output modalitiesTextText
Context window1,000K200K
Total parameters401.6BUnknown
Active parameters17BUnknown
LicenseotherUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessOpenrouter (Standard)Openai (Standard), Openrouter (Standard)
Capabilitieschat, generation, toolschat, generation, reasoning, structured_outputs, tools

14 comparable fields · 10 material differences · Pair passes the primary-source comparison gate

Llama 4 Maverick 17B 128E Instruct Capabilities

chatgenerationtools
Input price$0.20
Output price$0.696
Serving providers1
Canonical IDmeta-llama/Llama-4-Maverick-17B-128E-Instruct

o3 Capabilities

chatgenerationreasoningstructured outputstools
Input price$1.00
Output price$4.00
Serving providers2
Canonical IDopenai/o3

Internal Comparison Graph

Related Comparisons

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Primary Evidence

Sources and Freshness

Questions

Llama 4 Maverick 17B 128E Instruct vs o3 FAQs

Is Llama 4 Maverick 17B 128E Instruct or o3 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Maverick 17B 128E Instruct and o3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 4 Maverick 17B 128E Instruct or o3?+

Llama 4 Maverick 17B 128E Instruct is $0.20 and o3 is $1.00 per million tokens, so Llama 4 Maverick 17B 128E Instruct is cheaper on this metric. Llama 4 Maverick 17B 128E Instruct is $0.696 and o3 is $4.00 per million tokens, so Llama 4 Maverick 17B 128E Instruct is cheaper on this metric.

Which has a larger context window, Llama 4 Maverick 17B 128E Instruct or o3?+

Llama 4 Maverick 17B 128E Instruct has the larger sourced context window. Llama 4 Maverick 17B 128E Instruct supports 1,000K and o3 supports 200K.

Which performs better in benchmarks, Llama 4 Maverick 17B 128E Instruct or o3?+

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

Can Llama 4 Maverick 17B 128E Instruct or o3 be self-hosted?+

Llama 4 Maverick 17B 128E Instruct is the only model in this pair currently marked as self-hostable. Llama 4 Maverick 17B 128E Instruct is open weight; o3 is not marked open weight.

Can Llama 4 Maverick 17B 128E Instruct and o3 understand images?+

Llama 4 Maverick 17B 128E Instruct is documented with image input; o3 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Llama 4 Maverick 17B 128E Instruct or o3?+

Neither has a larger sourced maximum output. Llama 4 Maverick 17B 128E Instruct is — and o3 is 100K.

Do Llama 4 Maverick 17B 128E Instruct and o3 support reasoning and tool use?+

Llama 4 Maverick 17B 128E Instruct: tool calling and image input. o3: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 4 Maverick 17B 128E Instruct or o3?+

Llama 4 Maverick 17B 128E Instruct has 1 sourced provider route; o3 has 2, so o3 has broader tracked availability.

Which offers better value, Llama 4 Maverick 17B 128E Instruct or o3?+

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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