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DeepSeek V4 Flash 0423 vs Muse Glimmer 30B

DeepSeek V4 Flash 0423 leads Muse Glimmer 30B on the Artificial Analysis Intelligence Index, 24.4 to 17.5, and DeepSeek V4 Flash 0423 costs 4.8x less per output token ($0.28 vs $1.35 per million). Updated October 22, 2026; 5 benchmarks have a result for both.

DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
4
Muse Glimmer 30BMeta
Coding
No data
Overall
No data
Output $/M
$1.35
1
vs boards won of 5 shared

DeepSeek V4 Flash 0423 or Muse Glimmer 30B: which to pick

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

Pick DeepSeek V4 Flash 0423 for output tokens 4.8x cheaper ($0.28 vs $1.35 per million) and a larger context window (1.05M against 131K tokens).

Shared results
5
DeepSeek V4 Flash 0423 only
44
Muse Glimmer 30B only
0
Like-for-like categories
4 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
DeepSeek V4 Flash 0423 not benchmarked, Muse Glimmer 30B not benchmarked.
Widest category
Agentic work, 17.8 points apart on average over 1 shared benchmark.
Widest single gap
AA Agentic Index: DeepSeek V4 Flash 0423 26.3 against Muse Glimmer 30B 8.5, 17.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against Muse Glimmer 30B $1.35 per million output tokens, 4.8x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M 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
CategoryDeepSeek V4 Flash 0423BarsMuse Glimmer 30BTies
Coding11
Intelligence10
Agentic work10
Web design10
All shared boards41
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
Coding benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.049.0DeepSeek V4 Flash 0423
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2962.5Muse Glimmer 30B
LMArena Text: coding1457Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: software and IT1453Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML1558Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
AA Intelligence Index24.417.5DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V4 Flash 0423 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
AA Agentic Index26.38.5DeepSeek V4 Flash 0423
Neither model has a result on the other 40 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts1444Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: expert1441Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts in English1449Not measuredOnly DeepSeek V4 Flash 0423 measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 17 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Math benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
LMArena Text: math1426Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: mathematical work1432Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 11 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
LMArena Text: science1446Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: medicine and healthcare1448Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: legal and government1439Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: business and finance1425Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 14 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index10
Web design benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
Design Arena: websites1207Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: UI components1162Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: game dev11961144DeepSeek V4 Flash 0423
Design Arena: data viz1127Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: 3D1188Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: all code categories1205Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: SVG1155Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: ASCII art1109Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
General benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse Glimmer 30BLeader
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text1432Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: instruction following1421Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: creative writing1403Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: English1441Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: non-English1419Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Chinese1463Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: German1419Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Japanese1389Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Korean1383Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: French1439Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Spanish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Russian1427Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Polish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: multi-turn1449Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: longer queries1434Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: writing and language1410Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: entertainment and media1400Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0423 and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash 0423Muse 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

DeepSeek V4 Flash 0423$0.0003Fits in one request
Muse Glimmer 30B$0.0010Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
Muse Glimmer 30B$0.020Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
Muse Glimmer 30B$0.079Exceeds the context window

DeepSeek V4 Flash 0423 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 DeepSeek V4 Flash 0423 and Muse Glimmer 30B
SpecificationDeepSeek V4 Flash 0423Meta Muse Glimmer 30B
MakerDeepSeekMeta
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026August 9, 2026
Context window1.05M131K
Input $/Mtok$0.14$0.325
Output $/Mtok$0.28$1.35
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Muse Glimmer 30B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 4.8x cheaper ($0.28 vs $1.35 per million) and a larger context window (1.05M against 131K tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or Muse Glimmer 30B?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 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, DeepSeek V4 Flash 0423 or Muse Glimmer 30B?

DeepSeek V4 Flash 0423, with 1.05M tokens against 131K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs Muse Glimmer 30B comparison based on?

5 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark 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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