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DeepSeek V4 Flash Vision Exp vs Muse Glimmer 30B

DeepSeek V4 Flash Vision Exp leads Muse Glimmer 30B on the Artificial Analysis Intelligence Index, 34.8 to 17.5, at about the same output price ($1.32 vs $1.35 per million). Updated October 22, 2026; 3 benchmarks have a result for both.

DeepSeek V4 Flash Vision ExpDeepSeek
Coding
No data
Overall
56.4
Output $/M
$1.32
3
Muse Glimmer 30BMeta
Coding
No data
Overall
No data
Output $/M
$1.35
0
vs boards won of 3 shared

DeepSeek V4 Flash Vision Exp 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 Vision Exp for output tokens 1.0x cheaper ($1.32 vs $1.35 per million) and a larger context window (1.05M against 131K tokens).

Shared results
3
DeepSeek V4 Flash Vision Exp only
11
Muse Glimmer 30B only
2
Like-for-like categories
3 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 Vision Exp not benchmarked, Muse Glimmer 30B not benchmarked.
Widest category
Agentic work, 39.0 points apart on average over 1 shared benchmark.
Widest single gap
AA Agentic Index: DeepSeek V4 Flash Vision Exp 47.5 against Muse Glimmer 30B 8.5, 39.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash Vision Exp $1.32 against Muse Glimmer 30B $1.35 per million output tokens, 1.0x apart.
Context window
DeepSeek V4 Flash Vision Exp 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 Vision ExpBarsMuse Glimmer 30BTies
Coding10
Intelligence10
Agentic work10
All shared boards30
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
LiveBench coding37.6%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
AA Coding Index65.049.0DeepSeek V4 Flash Vision Exp
SciCode49.7%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
ALE-BenchNot measured962.5Only Muse Glimmer 30B measured
Neither model has a result on the other 39 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
AA Intelligence Index34.817.5DeepSeek V4 Flash Vision Exp
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
AA Agentic Index47.58.5DeepSeek V4 Flash Vision Exp
LiveBench research69.2%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
LiveBench browser64.0%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
LiveBench long agentic39.0%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
Neither model has a result on the other 38 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Reasoning benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
LiveBench reasoning85.4%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
GPQA Diamond (Artificial Analysis run)91.3%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
Humanity's Last Exam (Artificial Analysis run)34.5%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
Neither model has a result on the other 20 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
Neither model has a result on 14 boards here
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Knowledge benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
Neither model has a result on 20 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Web design benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
Design Arena: game devNot measured1132Only Muse Glimmer 30B measured
LiveBench design70.7%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
Neither model has a result on the other 7 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
General benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse Glimmer 30BLeader
LiveBench data analysis79.5%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
Long context reasoning (AA-LCR)81.3%Not measuredOnly DeepSeek V4 Flash Vision Exp measured
Neither model has a result on the other 46 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash Vision Exp and Muse Glimmer 30B
BenchmarkDeepSeek V4 Flash Vision ExpMuse 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 Vision Exp$0.0011Fits in one request
Muse Glimmer 30B$0.0010Fits in one request

Muse Glimmer 30B costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash Vision Exp$0.026Fits in one request
Muse Glimmer 30B$0.020Fits in one request

Muse Glimmer 30B costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash Vision Exp$0.101Fits in one request
Muse Glimmer 30B$0.079Exceeds the context window

Muse Glimmer 30B 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 Vision Exp and Muse Glimmer 30B
SpecificationDeepSeek V4 Flash Vision ExpMeta Muse Glimmer 30B
MakerDeepSeekMeta
WeightsOpen weightsOpen weights
ReleasedAugust 21, 2026August 9, 2026
Context window1.05M131K
Input $/Mtok$0.44$0.325
Output $/Mtok$1.32$1.35
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash Vision Exp 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 Vision Exp for output tokens 1.0x cheaper ($1.32 vs $1.35 per million) and a larger context window (1.05M against 131K tokens).

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

DeepSeek V4 Flash Vision Exp costs $0.44 per million input tokens and $1.32 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 Vision Exp or Muse Glimmer 30B?

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

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

3 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash Vision Exp'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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