Model comparison

Muse Glimmer 30B vs Qwen3.8 Max

Updated August 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Muse Glimmer 30B

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Agentic work
Tool use, computer use, and multi-step task completion
Qwen3.8 Max
Qwen3.8 Max leads on the same 1 weighted benchmark row.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Qwen3.8 Max
Qwen3.8 Max has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Muse Glimmer 30B does not fit this workload in one request. Muse Glimmer 30B has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

5 Muse Glimmer 30B only

9 Shared

43 Qwen3.8 Max only

Shared results: 9
Muse Glimmer 30B only: 5
Qwen3.8 Max only: 43
Like-for-like categories: 3 / 8

1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Like-for-like

Muse Glimmer 30B: 65.9
Qwen3.8 Max: 86.1
Weighted basis: 1 vs 1 rows
Reading: Qwen3.8 Max leads

Multimodal

Like-for-like

Muse Glimmer 30B: 75.7
Qwen3.8 Max: 86.3
Weighted basis: 2 vs 2 rows
Reading: Qwen3.8 Max leads

Instruction following

Like-for-like

Muse Glimmer 30B: 77.0
Qwen3.8 Max: 82.8
Weighted basis: 1 vs 1 rows
Reading: Qwen3.8 Max leads

Coding

Directional only

Muse Glimmer 30B: 57.8
Qwen3.8 Max: 67.7
Weighted basis: 3 vs 1 rows
Reading: Directional only

Reasoning

Not comparable

Muse Glimmer 30B: Not measured
Qwen3.8 Max: 78.3
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Knowledge

Not comparable

Muse Glimmer 30B: Not measured
Qwen3.8 Max: 50.2
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Math

Not comparable

Muse Glimmer 30B: 94.7
Qwen3.8 Max: Not measured
Weighted basis: 1 vs 0 rows
Reading: Not comparable

Multilingual

Not comparable

Muse Glimmer 30B: Not measured
Qwen3.8 Max: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Muse Glimmer 30B and Qwen3.8 Max
Category	Muse Glimmer 30B	Qwen3.8 Max	Weighted basis	Reading
Agentic	65.9	86.1	Like-for-like1 vs 1 rows	Qwen3.8 Max leads
Multimodal	75.7	86.3	Like-for-like2 vs 2 rows	Qwen3.8 Max leads
Instruction following	77.0	82.8	Like-for-like1 vs 1 rows	Qwen3.8 Max leads
Coding	57.8	67.7	Directional only3 vs 1 rows	Directional only
Reasoning	Not measured	78.3	Not comparable0 vs 2 rows	Not comparable
Knowledge	Not measured	50.2	Not comparable0 vs 2 rows	Not comparable
Math	94.7	Not measured	Not comparable1 vs 0 rows	Not comparable
Multilingual	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

OSWorld-Verified
Agentic
Muse Glimmer 30B: 65.9%Qwen3.8 Max: 86.1%Normalized gap 20.2Muse Glimmer 30B source Qwen3.8 Max source
SWE-bench Pro
Coding
Muse Glimmer 30B: 51.2%Qwen3.8 Max: 67.7%Normalized gap 16.5Muse Glimmer 30B source Qwen3.8 Max source
CharXiv
Multimodal
Muse Glimmer 30B: 78.8%Qwen3.8 Max: 93.5%Normalized gap 14.7Muse Glimmer 30B source Qwen3.8 Max source
MMMU-Pro
Multimodal
Muse Glimmer 30B: 74%Qwen3.8 Max: 82.3%Normalized gap 8.3Muse Glimmer 30B source Qwen3.8 Max source
IFBench
Instruction following
Muse Glimmer 30B: 77%Qwen3.8 Max: 82.8%Normalized gap 5.8Muse Glimmer 30B source Qwen3.8 Max source

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Muse Glimmer 30B: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.8 Max: API rate not published; Fits in one request

Muse Glimmer 30B has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Muse Glimmer 30B: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.8 Max: API rate not published; Fits in one request

Muse Glimmer 30B has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Muse Glimmer 30B: Self-hosted; infrastructure cost varies; Does not fit in one request; Cached-input rate unavailable
Qwen3.8 Max: API rate not published; Fits in one request; Cached-input rate unavailable

Muse Glimmer 30B does not fit this workload in one request. Muse Glimmer 30B has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationMuse Glimmer 30BQwen3.8 Max

Context window

Maximum documented context; output-token limits may be lower.

Muse Glimmer 30B

131K

Qwen3.8 Max

Alibaba Cloud Model Studio pricing

API model ID

Muse Glimmer 30B

Not sourced

Qwen3.8 Max

qwen3.8-max

Alibaba Cloud Model Studio pricing

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Muse Glimmer 30B

No comparable hosted API rate

Qwen3.8 Max

No comparable hosted API rate

Alibaba Cloud Model Studio pricing

Documented inputs

Muse Glimmer 30B

Not sourced

Qwen3.8 Max

Not sourced

Documented outputs

Muse Glimmer 30B

Not sourced

Qwen3.8 Max

Not sourced

Provider availability

Muse Glimmer 30B

Not sourced

Qwen3.8 Max

Not sourced

Reasoning profile

Muse Glimmer 30B

Reasoning

Qwen3.8 Max

Reasoning

Weight access

Muse Glimmer 30B

Open Weight

Qwen3.8 Max

Proprietary

License

Muse Glimmer 30B

Open Weight

Qwen3.8 Max

Proprietary

Release date

Muse Glimmer 30B

2026-08-10

Qwen3.8 Max

2026-08-03

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Qwen3.8 Max has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence57 rows

Agentic

MCP Atlas
Muse Glimmer 30B75.5%
Source
Qwen3.8 Max—
Not directly comparable
DeepSearchQA
Muse Glimmer 30B74.6%
Source
Qwen3.8 Max—
Not directly comparable
skillsBench
Muse Glimmer 30B44.3%
Source
Qwen3.8 Max70.2%
Source
Qwen3.8 Max leads this result
OSWorld-Verified
Muse Glimmer 30B65.9%
Source
Qwen3.8 Max86.1%
Source
Qwen3.8 Max leads this result
Terminal-Bench 2.1
Muse Glimmer 30B—
Qwen3.8 Max86.6%
Source
Not directly comparable
CoWorkBench
Muse Glimmer 30B—
Qwen3.8 Max74.8%
Source
Not directly comparable
JobBench
Muse Glimmer 30B—
Qwen3.8 Max53.4%
Source
Not directly comparable
Agents' Last Exam
Muse Glimmer 30B—
Qwen3.8 Max52.4%
Source
Not directly comparable
AutomationBench
Muse Glimmer 30B—
Qwen3.8 Max27.3%
Source
Not directly comparable
Toolathlon-Verified
Muse Glimmer 30B—
Qwen3.8 Max72.5%
Source
Not directly comparable
WideResearch
Muse Glimmer 30B—
Qwen3.8 Max81.9%
Source
Not directly comparable
HLE w/ tools
Muse Glimmer 30B—
Qwen3.8 Max56.2%
Source
Not directly comparable
OSWorld 2.0
Muse Glimmer 30B—
Qwen3.8 Max19.4%
Source
Not directly comparable
WebArena-Verified
Muse Glimmer 30B—
Qwen3.8 Max66.8%
Source
Not directly comparable
AndroidWorld
Muse Glimmer 30B—
Qwen3.8 Max85.3%
Source
Not directly comparable
MobileWorld
Muse Glimmer 30B—
Qwen3.8 Max77.8%
Source
Not directly comparable

Coding

SWE-bench Pro
Muse Glimmer 30B51.2%
Source
Qwen3.8 Max67.7%
Source
Qwen3.8 Max leads this result
SWE-bench Verified
Muse Glimmer 30B76%
Source
Qwen3.8 Max—
Not directly comparable
Terminal-Bench 2.1
Muse Glimmer 30B51.7%
Source
Qwen3.8 Max86.6%
Source
Qwen3.8 Max leads this result
SciCode
Muse Glimmer 30B43.6%
Source
Qwen3.8 Max—
Not directly comparable
deepSwe
Muse Glimmer 30B—
Qwen3.8 Max56.6%
Source
Not directly comparable
NL2Repo
Muse Glimmer 30B—
Qwen3.8 Max55.9%
Source
Not directly comparable
FrontierSWE
Muse Glimmer 30B—
Qwen3.8 Max73.5%
Source
Not directly comparable
MLS-Bench Lite
Muse Glimmer 30B—
Qwen3.8 Max41.0%
Source
Not directly comparable
PaperBench
Muse Glimmer 30B—
Qwen3.8 Max93.0%
Source
Not directly comparable

Reasoning

MRCRv2
Muse Glimmer 30B—
Qwen3.8 Max92.9%
Source
Not directly comparable
LongBench v2
Muse Glimmer 30B—
Qwen3.8 Max66.3%
Source
Not directly comparable

Knowledge

GPQA
Muse Glimmer 30B—
Qwen3.8 Max92.6%
Source
Not directly comparable
GPQA-D
Muse Glimmer 30B—
Qwen3.8 Max92.6%
Source
Not directly comparable
HLE
Muse Glimmer 30B—
Qwen3.8 Max43.6%
Source
Not directly comparable
HLE w/o tools
Muse Glimmer 30B—
Qwen3.8 Max43.6%
Source
Not directly comparable

Math

AIME26
Muse Glimmer 30B94.7%
Source
Qwen3.8 Max—
Not directly comparable

Multimodal

CharXiv
Muse Glimmer 30B78.8%
Source
Qwen3.8 Max93.5%
Source
Qwen3.8 Max leads this result
ScreenSpot Pro
Muse Glimmer 30B75.4%
Source
Qwen3.8 Max84.5%
Source
Qwen3.8 Max leads this result
OmniDocBench 1.5
Muse Glimmer 30B75.8%
Source
Qwen3.8 Max92.1%
Source
Qwen3.8 Max leads this result
MMMU-Pro
Muse Glimmer 30B74%
Source
Qwen3.8 Max82.3%
Source
Qwen3.8 Max leads this result
MathVision
Muse Glimmer 30B—
Qwen3.8 Max95.2%
Source
Not directly comparable
MathVision w/ Python
Muse Glimmer 30B—
Qwen3.8 Max97.7%
Source
Not directly comparable
BabyVision
Muse Glimmer 30B—
Qwen3.8 Max82.0%
Source
Not directly comparable
BabyVision w/ Python
Muse Glimmer 30B—
Qwen3.8 Max91.3%
Source
Not directly comparable
ZeroBench
Muse Glimmer 30B—
Qwen3.8 Max24.0%
Source
Not directly comparable
ZeroBench w/ Python
Muse Glimmer 30B—
Qwen3.8 Max49.0%
Source
Not directly comparable
MedXpertQA (MM)
Muse Glimmer 30B—
Qwen3.8 Max80.4%
Source
Not directly comparable
Vision2Web
Muse Glimmer 30B—
Qwen3.8 Max69.0%
Source
Not directly comparable
CharXiv w/o tools
Muse Glimmer 30B—
Qwen3.8 Max88.4%
Source
Not directly comparable
OCRBench V2
Muse Glimmer 30B—
Qwen3.8 Max74.2%
Source
Not directly comparable
CC-OCR
Muse Glimmer 30B—
Qwen3.8 Max79.6%
Source
Not directly comparable
RealWorldQA
Muse Glimmer 30B—
Qwen3.8 Max88.0%
Source
Not directly comparable
ERQA
Muse Glimmer 30B—
Qwen3.8 Max77.8%
Source
Not directly comparable
SimpleVQA
Muse Glimmer 30B—
Qwen3.8 Max75.0%
Source
Not directly comparable
PerceptionBench
Muse Glimmer 30B—
Qwen3.8 Max63.5%
Source
Not directly comparable
Video-MME (with subtitle)
Muse Glimmer 30B—
Qwen3.8 Max90.4%
Source
Not directly comparable
VideoMMMU
Muse Glimmer 30B—
Qwen3.8 Max88.7%
Source
Not directly comparable
MMVU
Muse Glimmer 30B—
Qwen3.8 Max82.4%
Source
Not directly comparable
MLVU (M-Avg)
Muse Glimmer 30B—
Qwen3.8 Max90.8%
Source
Not directly comparable
LVBench
Muse Glimmer 30B—
Qwen3.8 Max81.8%
Source
Not directly comparable

Instruction following

IFBench
Muse Glimmer 30B77%
Source
Qwen3.8 Max82.8%
Source
Qwen3.8 Max leads this result

Frequently asked questions

Which is better, Muse Glimmer 30B or Qwen3.8 Max?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Muse Glimmer 30B or Qwen3.8 Max?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Muse Glimmer 30B or Qwen3.8 Max?

Qwen3.8 Max leads the like-for-like agentic tasks comparison across 1 shared weighted benchmark row.

Which costs less, Muse Glimmer 30B or Qwen3.8 Max?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Muse Glimmer 30B or Qwen3.8 Max?

Qwen3.8 Max has the larger documented context window: 1M, compared with 131K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 10, 2026

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Muse Glimmer 30B vs Qwen3.8 Max

Which one for your work

Agentic work

Long documents

Coding work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Multimodal

Instruction following

Coding

Reasoning

Knowledge

Math

Multilingual

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multimodal

Instruction following

Frequently asked questions

Which is better, Muse Glimmer 30B or Qwen3.8 Max?

Which is better for coding, Muse Glimmer 30B or Qwen3.8 Max?

Which is better for agentic tasks, Muse Glimmer 30B or Qwen3.8 Max?

Which costs less, Muse Glimmer 30B or Qwen3.8 Max?

Which has the larger context window, Muse Glimmer 30B or Qwen3.8 Max?

Related comparisons

Watch Muse Glimmer 30B vs Qwen3.8 Max