Muse Glimmer 30B vs GPT-5.2 Pro

At a Glance

Compare
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.30Deepinfra · Sep 22, 2026$21.00Openai · Sep 3, 2026
Output priceFrom · USD / 1M tokens$1.20Deepinfra · Sep 22, 2026$168.00Openai · Sep 3, 2026
Context windowMaximum documented tokens131K400K
Model facts checkedSep 3, 2026View model evidence →Sep 3, 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

FieldMuse Glimmer 30BGPT-5.2 Pro
DeveloperMetaOpenAI
FamilyMuse GlimmerGpt 5 2
ModelMuse Glimmer 30BGPT-5.2 Pro
VersionMuse Glimmer 30BGPT-5.2 Pro
Lifecycleactiveactive
Released2026-08-092025-12-11
Knowledge cutoff2026-01-042025-08-31
Input modalitiesText, ImageText, Image
Output modalitiesTextText
Context window131K400K
Total parameters29.8BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard)Openai (Standard), Openrouter (Standard)
Capabilitieschat, generation, reasoning, structured_outputs, toolschat, generation, reasoning, structured_outputs, tools

Muse Glimmer 30B Capabilities

chatgenerationreasoningstructured outputstools
Serving providers3
Canonical IDmeta-models/Muse-Glimmer-30B

GPT-5.2 Pro Capabilities

chatgenerationreasoningstructured outputstools
Serving providers2
Canonical IDopenai/gpt-5.2-pro

Primary Evidence

Sources and Freshness

Questions

Muse Glimmer 30B vs GPT-5.2 Pro FAQs

Is Muse Glimmer 30B or GPT-5.2 Pro better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Muse Glimmer 30B and GPT-5.2 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Muse Glimmer 30B or GPT-5.2 Pro?+

Muse Glimmer 30B is $0.30 and GPT-5.2 Pro is $21.00 per million tokens, so Muse Glimmer 30B is cheaper on this metric. Muse Glimmer 30B is $1.20 and GPT-5.2 Pro is $168.00 per million tokens, so Muse Glimmer 30B is cheaper on this metric.

Which has a larger context window, Muse Glimmer 30B or GPT-5.2 Pro?+

GPT-5.2 Pro has the larger sourced context window. Muse Glimmer 30B supports 131K and GPT-5.2 Pro supports 400K.

Which performs better in benchmarks, Muse Glimmer 30B or GPT-5.2 Pro?+

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

Can Muse Glimmer 30B or GPT-5.2 Pro be self-hosted?+

Muse Glimmer 30B is the only model in this pair currently marked as self-hostable. Muse Glimmer 30B is open weight; GPT-5.2 Pro is not marked open weight.

Can Muse Glimmer 30B and GPT-5.2 Pro understand images?+

Muse Glimmer 30B is documented with image input; GPT-5.2 Pro is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Muse Glimmer 30B or GPT-5.2 Pro?+

Neither has a larger sourced maximum output. Muse Glimmer 30B is — and GPT-5.2 Pro is 128K.

Do Muse Glimmer 30B and GPT-5.2 Pro support reasoning and tool use?+

Muse Glimmer 30B: reasoning, tool calling, and image input. GPT-5.2 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Muse Glimmer 30B or GPT-5.2 Pro?+

Muse Glimmer 30B has 3 sourced provider routes; GPT-5.2 Pro has 2, so Muse Glimmer 30B has broader tracked availability.

Which offers better value, Muse Glimmer 30B or GPT-5.2 Pro?+

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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