Agentic
Like-for-like- Claude Sonnet 5
- 65.8
- Supported · #11/152
- Muse Spark
- 57.7
- Supported · #32/152
- Basis
- BenchAlign lane · 6 vs 5 public rows
- Reading
- Claude Sonnet 5 leads · intervals overlap
Claude Sonnet 5 vs Muse Spark
Updated September 8, 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 estimate, 69.8 versus 67.67, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
6 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.
Coding work
Code generation, repair, and software-engineering tasks
Claude Sonnet 5
Claude Sonnet 5 leads on the public coding lane, 64.1 to 59.1, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Claude Sonnet 5
Claude Sonnet 5 leads on the public agentic lane, 65.8 to 57.7, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
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
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
A complete comparable API-rate estimate is not available for both models.
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.
18 Claude Sonnet 5 only
6 Shared
18 Muse Spark only
- Shared results
- 6
- Claude Sonnet 5 only
- 18
- Muse Spark only
- 18
- Like-for-like categories
- 3 / 8
1 category rests 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
Like-for-like- Claude Sonnet 5
- 64.1
- Supported · #13/151
- Muse Spark
- 59.1
- Supported · #26/151
- Basis
- BenchAlign lane · 10 vs 4 public rows
- Reading
- Claude Sonnet 5 leads · intervals overlap
Knowledge
Like-for-like- Claude Sonnet 5
- 66.7
- Supported · #20/182
- Muse Spark
- 65.6
- Supported · #24/182
- Basis
- BenchAlign lane · 6 vs 5 public rows
- Reading
- Claude Sonnet 5 leads · intervals overlap
Multimodal
Directional only- Claude Sonnet 5
- 77.5
- #13/48
- Muse Spark
- 77.5
- #14/48
- Basis
- Provisional lane · 1 vs 2 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Sonnet 5
- 77.4
- Unranked · 2 rankable rows
- Muse Spark
- 45.1
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 5
- Not ranked
- Muse Spark
- 55.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 5
- Not ranked
- Muse Spark
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 5
- Not ranked
- Muse Spark
- 93.2
- #8/121
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Sonnet 5 | Muse Spark | Basis | Reading |
|---|---|---|---|---|
| Agentic | 65.8Supported · #11/152 | 57.7Supported · #32/152 | Like-for-likeBenchAlign lane · 6 vs 5 public rows | Claude Sonnet 5 leads · intervals overlap |
| Coding | 64.1Supported · #13/151 | 59.1Supported · #26/151 | Like-for-likeBenchAlign lane · 10 vs 4 public rows | Claude Sonnet 5 leads · intervals overlap |
| Knowledge | 66.7Supported · #20/182 | 65.6Supported · #24/182 | Like-for-likeBenchAlign lane · 6 vs 5 public rows | Claude Sonnet 5 leads · intervals overlap |
| Multimodal | 77.5#13/48 | 77.5#14/48 | Directional onlyProvisional lane · 1 vs 2 weighted rows | Directional only |
| Reasoning | 77.4Unranked · 2 rankable rows | 45.1Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | Not ranked | 55.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 93.2#8/121 | Not comparableProvisional lane · 0 vs 0 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.
Terminal-Bench 2.0
Agentic
SWE-bench Pro
Coding
SWE-bench Verified
Coding
HLE
Knowledge
CharXiv
Multimodal
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 Spark
- API rate not published
- Fits in one request
Muse Spark 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 Spark
- API rate not published
- Fits in one request
Muse Spark 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 Spark
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Muse Spark 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 Spark
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 5
Muse Spark
262K
API model ID
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewMuse Spark
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 Spark
No comparable hosted API rate
Documented inputs
Claude Sonnet 5
text, image
Anthropic model overviewMuse Spark
Not sourced
Documented outputs
Claude Sonnet 5
Muse Spark
Not sourced
Provider availability
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewMuse Spark
Not sourced
Reasoning profile
Claude Sonnet 5
Reasoning
Muse Spark
Reasoning
Weight access
Claude Sonnet 5
Proprietary
Muse Spark
Proprietary
License
Claude Sonnet 5
Proprietary
Muse Spark
Proprietary
Release date
Claude Sonnet 5
2026-06-30
Muse Spark
2026-04-08
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 estimate, 69.8 versus 67.67, but the 90% score intervals 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 evidence42 rows
Agentic
Terminal-Bench 3.0
Claude Sonnet 514.6%SourceMuse Spark—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceMuse Spark59%SourceClaude Sonnet 5 leads this result
BrowseComp
Claude Sonnet 584.7%SourceMuse Spark—Not directly comparable
HLE w/ tools
Claude Sonnet 557.4%SourceMuse Spark—Not directly comparable
OSWorld-Verified
Claude Sonnet 581.2%SourceMuse Spark—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Sonnet 574.5%SourceMuse Spark—Not directly comparable
τ²-bench results
Claude Sonnet 5—Muse Spark91.5%SourceNot directly comparable
DeepSearchQA
Claude Sonnet 5—Muse Spark74.8%SourceNot directly comparable
CyberGym
Claude Sonnet 5—Muse Spark43.5%SourceNot directly comparable
Claw-Eval
Claude Sonnet 5—Muse Spark63.8%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Sonnet 585.2%SourceMuse Spark77.4%SourceClaude Sonnet 5 leads this result
SWE-bench Pro
Claude Sonnet 563.2%SourceMuse Spark52.4%SourceClaude Sonnet 5 leads this result
SWE Multilingual
Claude Sonnet 578.3%SourceMuse Spark—Not directly comparable
SWE Multimodal
Claude Sonnet 528.1%SourceMuse Spark—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceMuse Spark—Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 542.7%SourceMuse Spark—Not directly comparable
cursorBench32
Claude Sonnet 561.5%SourceMuse Spark—Not directly comparable
VulcanBench CII v1
Claude Sonnet 589.2%SourceMuse Spark—Not directly comparable
LiveCodeBench (Vals)
Claude Sonnet 582.4%SourceMuse Spark—Not directly comparable
SWE-bench (Vals)
Claude Sonnet 579.6%SourceMuse Spark—Not directly comparable
LiveCodeBench Pro
Claude Sonnet 5—Muse Spark80.0%SourceNot directly comparable
Vibe Code Bench
Claude Sonnet 5—Muse Spark19.67%SourceNot directly comparable
Reasoning
ARC-AGI-2
Claude Sonnet 5—Muse Spark42.5%SourceNot directly comparable
Knowledge
HLE
Claude Sonnet 557.4%SourceMuse Spark50.4%SourceClaude Sonnet 5 leads this result
HLE w/o tools
Claude Sonnet 543.2%SourceMuse Spark42.8%SourceClaude Sonnet 5 leads this result
HLE-Verified
Claude Sonnet 531.0%SourceMuse Spark—Not directly comparable
LABBench2
Claude Sonnet 580.1%SourceMuse Spark—Not directly comparable
GPQA Diamond (Vals)
Claude Sonnet 588.9%SourceMuse Spark—Not directly comparable
MMLU-Pro (Vals)
Claude Sonnet 587.5%SourceMuse Spark—Not directly comparable
GPQA-D
Claude Sonnet 5—Muse Spark89.5%SourceNot directly comparable
HealthBench Hard
Claude Sonnet 5—Muse Spark42.8%SourceNot directly comparable
MedXpertQA (Text)
Claude Sonnet 5—Muse Spark52.6%SourceNot directly comparable
Math
Multimodal
CharXiv
Claude Sonnet 588.3%SourceMuse Spark86.4%SourceClaude Sonnet 5 leads this result
CharXiv w/o tools
Claude Sonnet 577%SourceMuse Spark—Not directly comparable
MMMU-Pro
Claude Sonnet 5—Muse Spark80.4%SourceNot directly comparable
ERQA
Claude Sonnet 5—Muse Spark64.7%SourceNot directly comparable
SimpleVQA
Claude Sonnet 5—Muse Spark71.3%SourceNot directly comparable
ScreenSpot Pro
Claude Sonnet 5—Muse Spark84.1%SourceNot directly comparable
ZeroBench
Claude Sonnet 5—Muse Spark33.0%SourceNot directly comparable
MedXpertQA (MM)
Claude Sonnet 5—Muse Spark78.4%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Sonnet 5 or Muse Spark?
Claude Sonnet 5 has the higher public score estimate, 69.8 versus 67.67, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Claude Sonnet 5 or Muse Spark?
Claude Sonnet 5 leads the public coding lane, 64.1 to 59.1, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Claude Sonnet 5 or Muse Spark?
Claude Sonnet 5 leads the public agentic tasks lane, 65.8 to 57.7, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Claude Sonnet 5 or Muse Spark?
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 Spark?
Claude Sonnet 5 has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 8, 2026
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