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GPT-4o-mini vs Muse Glimmer 30B

Muse Glimmer 30B leads GPT-4o-mini on the Artificial Analysis Intelligence Index, 17.5 to 6.7, and GPT-4o-mini costs 2.3x less per output token ($0.60 vs $1.35 per million). Updated October 22, 2026; 2 benchmarks have a result for both.

GPT-4o-miniOpenAI
Coding
No data
Overall
No data
Output $/M
$0.60
0
Muse Glimmer 30BMeta
Coding
No data
Overall
No data
Output $/M
$1.35
2
vs boards won of 2 shared

GPT-4o-mini or Muse Glimmer 30B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GPT-4o-mini for output tokens 2.3x cheaper ($0.60 vs $1.35 per million) and work measured by AA Coding Index or AA Intelligence Index, where it leads.

Shared results
2
GPT-4o-mini only
27
Muse Glimmer 30B only
3
Like-for-like categories
2 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GPT-4o-mini not benchmarked, Muse Glimmer 30B not benchmarked.
Widest category
Coding, 37.6 points apart on average over 1 shared benchmark.
Widest single gap
AA Coding Index: GPT-4o-mini 11.4 against Muse Glimmer 30B 49.0, 37.6 points apart on a 0 to 100 scale.
Output price
GPT-4o-mini $0.60 against Muse Glimmer 30B $1.35 per million output tokens, 2.3x apart.
Context window
GPT-4o-mini takes 128K tokens, Muse Glimmer 30B 131K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGPT-4o-miniBarsMuse Glimmer 30BTies
Coding01
Intelligence01
All shared boards02
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
AA Coding Index11.449.0Muse Glimmer 30B
LiveCodeBench (Vals AI)26.4%Not measuredOnly GPT-4o-mini measured
LiveCodeBench (Artificial Analysis run)23.4%Not measuredOnly GPT-4o-mini measured
ALE-BenchNot measured962.5Only Muse Glimmer 30B measured
SciCode1.5%Not measuredOnly GPT-4o-mini measured
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
AA Intelligence Index6.717.5Muse Glimmer 30B
Epoch Capabilities Index126.5Not measuredOnly GPT-4o-mini measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
AA Agentic IndexNot measured8.5Only Muse Glimmer 30B measured
Neither model has a result on the other 40 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Reasoning benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
GPQA Diamond44.2%Not measuredOnly GPT-4o-mini measured
MMMU Pro (Vals AI)56.6%Not measuredOnly GPT-4o-mini measured
GPQA Diamond (Artificial Analysis run)42.6%Not measuredOnly GPT-4o-mini measured
Humanity's Last Exam (Artificial Analysis run)4.2%Not measuredOnly GPT-4o-mini measured
ARC-AGI-20.0%Not measuredOnly GPT-4o-mini measured
Kagi LLM Benchmark28.8%Not measuredOnly GPT-4o-mini measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
AIME11.5%Not measuredOnly GPT-4o-mini measured
MATH 500 (Vals AI)72.6%Not measuredOnly GPT-4o-mini measured
MGSM (Vals AI)86.2%Not measuredOnly GPT-4o-mini measured
AA Math Index14.7Not measuredOnly GPT-4o-mini measured
AIME 2025 (Artificial Analysis run)14.7%Not measuredOnly GPT-4o-mini measured
GSM8K91.3%Not measuredOnly GPT-4o-mini measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
MMLU Pro62.7%Not measuredOnly GPT-4o-mini measured
CorpFin (Vals AI)45.5%Not measuredOnly GPT-4o-mini measured
TaxEval (Vals AI)60.5%Not measuredOnly GPT-4o-mini measured
MortgageTax (Vals AI)54.5%Not measuredOnly GPT-4o-mini measured
MedQA (Vals AI)72.4%Not measuredOnly GPT-4o-mini measured
MMLU Pro (Artificial Analysis run)64.8%Not measuredOnly GPT-4o-mini measured
MMLU81.8%Not measuredOnly GPT-4o-mini measured
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Web design benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
Design Arena: game devNot measured1144Only Muse Glimmer 30B measured
Neither model has a result on the other 8 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
General benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
IFBench31.0%Not measuredOnly GPT-4o-mini measured
DTBench54.4%Not measuredOnly GPT-4o-mini measured
LMCA10.4%Not measuredOnly GPT-4o-mini measured
PIQA88.7%Not measuredOnly GPT-4o-mini measured
Neither model has a result on the other 42 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4o-mini and Muse Glimmer 30B
BenchmarkGPT-4o-miniMuse Glimmer 30BLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GPT-4o-mini$0.0004Fits in one request
Muse Glimmer 30B$0.0010Fits in one request

GPT-4o-mini costs less

Repository review

50K input + 3K output tokens

GPT-4o-mini$0.0093Fits in one request
Muse Glimmer 30B$0.020Fits in one request

GPT-4o-mini costs less

Agent loop

200K input + 10K output tokens

GPT-4o-mini$0.036Exceeds the context window
Muse Glimmer 30B$0.079Exceeds the context window

GPT-4o-mini costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GPT-4o-mini and Muse Glimmer 30B
SpecificationOpenAI GPT-4o-miniMeta Muse Glimmer 30B
MakerOpenAIMeta
WeightsNo public weights listedOpen weights
ReleasedJuly 18, 2024August 9, 2026
Context window128K131K
Input $/Mtok$0.15$0.325
Output $/Mtok$0.60$1.35
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o-mini better than Muse Glimmer 30B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o-mini for output tokens 2.3x cheaper ($0.60 vs $1.35 per million) and work measured by AA Coding Index or AA Intelligence Index, where it leads.

Which is cheaper, GPT-4o-mini or Muse Glimmer 30B?

GPT-4o-mini costs $0.15 per million input tokens and $0.60 per million output tokens; Muse Glimmer 30B costs $0.325 and $1.35. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4o-mini or Muse Glimmer 30B?

Muse Glimmer 30B, with 131K tokens against 128K.

How many benchmarks is the GPT-4o-mini vs Muse Glimmer 30B comparison based on?

2 benchmarks have a result for both models as of October 22, 2026. GPT-4o-mini's coding index rests on 0 independent benchmarks and Muse Glimmer 30B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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