Agentic
Directional only- Claude Sonnet 5
- 65.9
- Supported · #11/153
- Muse Glimmer 30B
- 43.1
- Estimated · #101/153
- Basis
- BenchAlign lane · 7 vs 4 public rows
- Reading
- Directional only
Claude Sonnet 5 vs Muse Glimmer 30B
Updated September 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Sonnet 5 has the higher public score, 69.92 versus 44.96, and the 90% score intervals do not overlap.
4 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Long documents
Prompts that approach the documented context limit
Claude Sonnet 5
Claude Sonnet 5 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
Muse Glimmer 30B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Muse Glimmer 30B is scored on Estimated evidence for agentic, so the reading is 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.
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.
22 Claude Sonnet 5 only
4 Shared
10 Muse Glimmer 30B only
- Shared results
- 4
- Claude Sonnet 5 only
- 22
- Muse Glimmer 30B only
- 10
- Like-for-like categories
- 0 / 8
4 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Coding
Directional only- Claude Sonnet 5
- 64.1
- Supported · #13/152
- Muse Glimmer 30B
- 48.3
- Estimated · #71/152
- Basis
- BenchAlign lane · 11 vs 4 public rows
- Reading
- Directional only
Knowledge
Directional only- Claude Sonnet 5
- 66.6
- Supported · #20/183
- Muse Glimmer 30B
- 47.2
- Estimated · #99/183
- Basis
- BenchAlign lane · 6 vs 0 public rows
- Reading
- Directional only
Multimodal
Directional only- Claude Sonnet 5
- 77.5
- #13/48
- Muse Glimmer 30B
- 46.4
- #40/48
- Basis
- Provisional lane · 1 vs 2 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Sonnet 5
- 77.4
- Unranked · 2 rankable rows
- Muse Glimmer 30B
- 78.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 5
- Not ranked
- Muse Glimmer 30B
- 76.3
- Unranked · 1 rankable row
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 5
- Not ranked
- Muse Glimmer 30B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 5
- Not ranked
- Muse Glimmer 30B
- 80.1
- #53/123
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | Claude Sonnet 5 | Muse Glimmer 30B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 65.9Supported · #11/153 | 43.1Estimated · #101/153 | Directional onlyBenchAlign lane · 7 vs 4 public rows | Directional only |
| Coding | 64.1Supported · #13/152 | 48.3Estimated · #71/152 | Directional onlyBenchAlign lane · 11 vs 4 public rows | Directional only |
| Knowledge | 66.6Supported · #20/183 | 47.2Estimated · #99/183 | Directional onlyBenchAlign lane · 6 vs 0 public rows | Directional only |
| Multimodal | 77.5#13/48 | 46.4#40/48 | Directional onlyProvisional lane · 1 vs 2 weighted rows | Directional only |
| Reasoning | 77.4Unranked · 2 rankable rows | 78.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 76.3Unranked · 1 rankable row | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 80.1#53/123 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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
Claude Sonnet 5: 81.2%Muse Glimmer 30B: 65.9%Normalized gap 15.3Claude Sonnet 5 source Muse Glimmer 30B sourceSWE-bench Pro
Coding
Claude Sonnet 5: 63.2%Muse Glimmer 30B: 51.2%Normalized gap 12.0Claude Sonnet 5 source Muse Glimmer 30B sourceCharXiv
Multimodal
Claude Sonnet 5: 88.3%Muse Glimmer 30B: 78.8%Normalized gap 9.5Claude Sonnet 5 source Muse Glimmer 30B sourceSWE-bench Verified
Coding
Claude Sonnet 5: 85.2%Muse Glimmer 30B: 76%Normalized gap 9.2Claude Sonnet 5 source Muse Glimmer 30B 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
- Claude Sonnet 5
- $0.007
- Fits in one request
- Muse Glimmer 30B
- Self-hosted; infrastructure cost varies
- Fits in one request
Muse Glimmer 30B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 5
- $0.13
- Fits in one request
- Muse Glimmer 30B
- Self-hosted; infrastructure cost varies
- Fits in one request
Muse Glimmer 30B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Sonnet 5
- $0.18
- Fits in one request
- Muse Glimmer 30B
- Self-hosted; infrastructure cost varies
- Does not fit 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.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Sonnet 5Muse Glimmer 30B
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 5
Muse Glimmer 30B
131K
API model ID
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewMuse Glimmer 30B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5
$0.2 per 1M cached input tokens
Claude API pricingMuse Glimmer 30B
No comparable hosted API rate
Documented inputs
Claude Sonnet 5
text, image
Anthropic model overviewMuse Glimmer 30B
Not sourced
Documented outputs
Claude Sonnet 5
Muse Glimmer 30B
Not sourced
Provider availability
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewMuse Glimmer 30B
Not sourced
Reasoning profile
Claude Sonnet 5
Reasoning
Muse Glimmer 30B
Reasoning
Weight access
Claude Sonnet 5
Proprietary
Muse Glimmer 30B
Open Weight
License
Claude Sonnet 5
Proprietary
Muse Glimmer 30B
Open Weight
Release date
Claude Sonnet 5
2026-06-30
Muse Glimmer 30B
2026-08-10
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
- Claude Sonnet 5 has the higher public score, 69.92 versus 44.96, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Claude Sonnet 5 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 evidence36 rows
Agentic
Terminal-Bench 3.0
Claude Sonnet 514.6%SourceMuse Glimmer 30B—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceMuse Glimmer 30B—Not directly comparable
BrowseComp
Claude Sonnet 584.7%SourceMuse Glimmer 30B—Not directly comparable
HLE w/ tools
Claude Sonnet 557.4%SourceMuse Glimmer 30B—Not directly comparable
OSWorld-Verified
Claude Sonnet 581.2%SourceMuse Glimmer 30B65.9%SourceClaude Sonnet 5 leads this result
Terminal-Bench 2.1 (Vals)
Claude Sonnet 574.5%SourceMuse Glimmer 30B—Not directly comparable
ApprenticeBench
Claude Sonnet 516%SourceMuse Glimmer 30B—Not directly comparable
MCP Atlas
Claude Sonnet 5—Muse Glimmer 30B75.5%SourceNot directly comparable
DeepSearchQA
Claude Sonnet 5—Muse Glimmer 30B74.6%SourceNot directly comparable
skillsBench
Claude Sonnet 5—Muse Glimmer 30B44.3%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Sonnet 585.2%SourceMuse Glimmer 30B76%SourceClaude Sonnet 5 leads this result
SWE-bench Pro
Claude Sonnet 563.2%SourceMuse Glimmer 30B51.2%SourceClaude Sonnet 5 leads this result
SWE Multilingual
Claude Sonnet 578.3%SourceMuse Glimmer 30B—Not directly comparable
SWE Multimodal
Claude Sonnet 528.1%SourceMuse Glimmer 30B—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceMuse Glimmer 30B—Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 542.7%SourceMuse Glimmer 30B—Not directly comparable
cursorBench32
Claude Sonnet 561.5%SourceMuse Glimmer 30B—Not directly comparable
VulcanBench CII v1
Claude Sonnet 589.2%SourceMuse Glimmer 30B—Not directly comparable
LiveCodeBench (Vals)
Claude Sonnet 582.4%SourceMuse Glimmer 30B—Not directly comparable
SWE-bench (Vals)
Claude Sonnet 579.6%SourceMuse Glimmer 30B—Not directly comparable
cursorBench40
Claude Sonnet 534.1%SourceMuse Glimmer 30B—Not directly comparable
Terminal-Bench 2.1
Claude Sonnet 5—Muse Glimmer 30B51.7%SourceNot directly comparable
SciCode
Claude Sonnet 5—Muse Glimmer 30B43.6%SourceNot directly comparable
Knowledge
HLE
Claude Sonnet 557.4%SourceMuse Glimmer 30B—Not directly comparable
HLE w/o tools
Claude Sonnet 543.2%SourceMuse Glimmer 30B—Not directly comparable
HLE-Verified
Claude Sonnet 531.0%SourceMuse Glimmer 30B—Not directly comparable
LABBench2
Claude Sonnet 580.1%SourceMuse Glimmer 30B—Not directly comparable
GPQA Diamond (Vals)
Claude Sonnet 588.9%SourceMuse Glimmer 30B—Not directly comparable
MMLU-Pro (Vals)
Claude Sonnet 587.5%SourceMuse Glimmer 30B—Not directly comparable
Math
AIME26
Claude Sonnet 5—Muse Glimmer 30B94.7%SourceNot directly comparable
Multimodal
CharXiv
Claude Sonnet 588.3%SourceMuse Glimmer 30B78.8%SourceClaude Sonnet 5 leads this result
CharXiv w/o tools
Claude Sonnet 577%SourceMuse Glimmer 30B—Not directly comparable
ScreenSpot Pro
Claude Sonnet 5—Muse Glimmer 30B75.4%SourceNot directly comparable
OmniDocBench 1.5
Claude Sonnet 5—Muse Glimmer 30B75.8%SourceNot directly comparable
MMMU-Pro
Claude Sonnet 5—Muse Glimmer 30B74%SourceNot directly comparable
Instruction following
IFBench
Claude Sonnet 5—Muse Glimmer 30B77%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Sonnet 5 or Muse Glimmer 30B?
Claude Sonnet 5 has the higher public score, 69.92 versus 44.96, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, Claude Sonnet 5 or Muse Glimmer 30B?
Claude Sonnet 5 scores higher for coding on the public lane, 64.1 to 48.3. Muse Glimmer 30B is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Claude Sonnet 5 or Muse Glimmer 30B?
Claude Sonnet 5 scores higher for agentic tasks on the public lane, 65.9 to 43.1. Muse Glimmer 30B is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Claude Sonnet 5 or Muse Glimmer 30B?
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, Claude Sonnet 5 or Muse Glimmer 30B?
Claude Sonnet 5 has the larger documented context window: 1M, compared with 131K.
Related comparisons
Last updated September 14, 2026
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