Agentic
Like-for-like- Claude Opus 4.8
- 63.1
- Supported · #13/154
- Muse Spark 1.2
- 61.0
- Supported · #16/154
- Basis
- BenchAlign lane · 12 vs 2 public rows
- Reading
- Claude Opus 4.8 leads · intervals overlap
Claude Opus 4.8 vs Muse Spark 1.2
Decision reading
Claude Opus 4.8 has the higher public score estimate, 72.17 versus 70.28, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Updated September 18, 2026. Rank says Claude Opus 4.8 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
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 Opus 4.8
Claude Opus 4.8 leads on the public coding lane, 66.3 to 60, 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 Opus 4.8
Claude Opus 4.8 leads on the public agentic lane, 63.1 to 61, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Muse Spark 1.2
Muse Spark 1.2 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Muse Spark 1.2
Muse Spark 1.2 has the lower estimated token cost for this stated workload. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Repository review cost
50K fresh input + 3K output tokens
Muse Spark 1.2
Muse Spark 1.2 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
66.3Claude Opus 4.860.0Muse Spark 1.2
Like-for-like · BenchAlign
Claude Opus 4.8 leads the like-for-like coding row, although the 90% intervals overlap.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
35 Claude Opus 4.8 only
3 Shared
5 Muse Spark 1.2 only
- Shared results
- 3
- Claude Opus 4.8 only
- 35
- Muse Spark 1.2 only
- 5
- Like-for-like categories
- 2 / 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 Opus 4.8
- 66.3
- Supported · #11/154
- Muse Spark 1.2
- 60.0
- Supported · #21/154
- Basis
- BenchAlign lane · 10 vs 5 public rows
- Reading
- Claude Opus 4.8 leads · intervals overlap
Knowledge
Directional only- Claude Opus 4.8
- 71.4
- Supported · #9/184
- Muse Spark 1.2
- 70.7
- Estimated · #10/184
- Basis
- BenchAlign lane · 6 vs 1 public rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Opus 4.8
- 55.5
- #18/20
- Muse Spark 1.2
- 75.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 4.8
- 65.2
- #2/7
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 3 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.8
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.8
- 87.7
- #3/48
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.8
- 74.0
- #60/124
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 4.8 | Muse Spark 1.2 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 63.1Supported · #13/154 | 61.0Supported · #16/154 | Like-for-likeBenchAlign lane · 12 vs 2 public rows | Claude Opus 4.8 leads · intervals overlap |
| Coding | 66.3Supported · #11/154 | 60.0Supported · #21/154 | Like-for-likeBenchAlign lane · 10 vs 5 public rows | Claude Opus 4.8 leads · intervals overlap |
| Knowledge | 71.4Supported · #9/184 | 70.7Estimated · #10/184 | Directional onlyBenchAlign lane · 6 vs 1 public rows | Directional only |
| Reasoning | 55.5#18/20 | 75.3Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Math | 65.2#2/7 | Not ranked | Not comparableProvisional lane · 3 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 87.7#3/48 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Instruction following | 74.0#60/124 | Not ranked | 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.
MMLU-Pro (Vals)
Knowledge
Claude Opus 4.8: 89.6%Muse Spark 1.2: 88.3%Normalized gap 1.3Claude Opus 4.8 source Muse Spark 1.2 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 Opus 4.8
- $0.0175
- Fits in one request
- Muse Spark 1.2
- $0.00338
- Fits in one request
Muse Spark 1.2 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 4.8
- $0.325
- Fits in one request
- Muse Spark 1.2
- $0.07525
- Fits in one request
Muse Spark 1.2 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Opus 4.8
- $1.35
- Fits in one request
- Cached input priced at the published list-input rate
- Muse Spark 1.2
- $0.0975
- Fits in one request
Muse Spark 1.2 has the lower modeled cost
Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 4.8Muse Spark 1.2
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.8
Muse Spark 1.2
API model ID
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewMuse Spark 1.2
muse-spark-1.2
Meta: Muse Spark 1.2 model pageCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 4.8
Not published
Muse Spark 1.2
$0.15 per 1M cached input tokens
Meta: Muse Spark 1.2 model pageDocumented inputs
Claude Opus 4.8
text, image
Anthropic model overviewMuse Spark 1.2
Not sourced
Documented outputs
Claude Opus 4.8
Muse Spark 1.2
Not sourced
Provider availability
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewMuse Spark 1.2
Not sourced
Reasoning profile
Claude Opus 4.8
Reasoning
Muse Spark 1.2
Reasoning
Weight access
Claude Opus 4.8
Proprietary
Muse Spark 1.2
Proprietary
License
Claude Opus 4.8
Proprietary
Muse Spark 1.2
Proprietary
Release date
Claude Opus 4.8
2026-05-28
Muse Spark 1.2
2026-08-05
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 Opus 4.8 has the higher public score estimate, 72.17 versus 70.28, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.325 vs $0.07525. Cache-heavy agent loop: $1.35 vs $0.0975.
- Context tradeoff
- Both models list 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 evidence43 rows
Agentic
Terminal-Bench 3.0
Claude Opus 4.821.1%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceMuse Spark 1.2—Not directly comparable
BrowseComp
Claude Opus 4.884.3%SourceMuse Spark 1.2—Not directly comparable
DeepSearchQA
Claude Opus 4.893.1%SourceMuse Spark 1.2—Not directly comparable
OSWorld-Verified
Claude Opus 4.883.4%SourceMuse Spark 1.2—Not directly comparable
Finance Agent v2
Claude Opus 4.853.9%SourceMuse Spark 1.2—Not directly comparable
MCP Atlas
Claude Opus 4.882.2%SourceMuse Spark 1.2—Not directly comparable
Toolathlon
Claude Opus 4.859.9%SourceMuse Spark 1.2—Not directly comparable
Gert Labs
Claude Opus 4.872.97%SourceMuse Spark 1.2—Not directly comparable
ResearchClawBench
Claude Opus 4.821.1%SourceMuse Spark 1.2—Not directly comparable
OSWorld 2.0
Claude Opus 4.820.6%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Opus 4.871.9%SourceMuse Spark 1.269.7%SourceClaude Opus 4.8 leads this result
Terminal-Bench 2.1
Claude Opus 4.8—Muse Spark 1.282.9%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Opus 4.888.6%SourceMuse Spark 1.2—Not directly comparable
SWE-bench Pro
Claude Opus 4.869.2%SourceMuse Spark 1.2—Not directly comparable
SWE Multilingual
Claude Opus 4.884.4%SourceMuse Spark 1.2—Not directly comparable
SWE Multimodal
Claude Opus 4.838.4%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.874.6%SourceMuse Spark 1.2—Not directly comparable
cursorBench31
Claude Opus 4.858.4%SourceMuse Spark 1.2—Not directly comparable
cursorBench32
Claude Opus 4.862.3%SourceMuse Spark 1.2—Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.846.5%SourceMuse Spark 1.2—Not directly comparable
LiveCodeBench (Vals)
Claude Opus 4.887.8%SourceMuse Spark 1.2—Not directly comparable
SWE-bench (Vals)
Claude Opus 4.888.6%SourceMuse Spark 1.286.6%SourceClaude Opus 4.8 leads this result
Terminal-Bench 2.1
Claude Opus 4.8—Muse Spark 1.282.9%SourceNot directly comparable
DeepSWE
Claude Opus 4.8—Muse Spark 1.259.3%SourceNot directly comparable
VulcanBench v3
Claude Opus 4.8—Muse Spark 1.287.0%SourceNot directly comparable
FrontierSWE v2
Claude Opus 4.8—Muse Spark 1.212.0%SourceNot directly comparable
Reasoning
Knowledge
GPQA
Claude Opus 4.893.6%SourceMuse Spark 1.2—Not directly comparable
GPQA-D
Claude Opus 4.893.6%SourceMuse Spark 1.2—Not directly comparable
HLE
Claude Opus 4.857.9%SourceMuse Spark 1.2—Not directly comparable
HLE w/o tools
Claude Opus 4.849.8%SourceMuse Spark 1.2—Not directly comparable
GPQA Diamond (Vals)
Claude Opus 4.892.4%SourceMuse Spark 1.2—Not directly comparable
MMLU-Pro (Vals)
Claude Opus 4.889.6%SourceMuse Spark 1.288.3%SourceClaude Opus 4.8 leads this result
Math
Multilingual
INCLUDE
Claude Opus 4.887.6%SourceMuse Spark 1.2—Not directly comparable
Multimodal
OfficeQA Pro
Claude Opus 4.866.2%SourceMuse Spark 1.2—Not directly comparable
ScreenSpot Pro
Claude Opus 4.887.9%SourceMuse Spark 1.2—Not directly comparable
CharXiv
Claude Opus 4.889.9%SourceMuse Spark 1.2—Not directly comparable
CharXiv w/o tools
Claude Opus 4.880.5%SourceMuse Spark 1.2—Not directly comparable
Questions
Which is better, Claude Opus 4.8 or Muse Spark 1.2?
Claude Opus 4.8 has the higher public score estimate, 72.17 versus 70.28, 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 Opus 4.8 or Muse Spark 1.2?
Claude Opus 4.8 leads the public coding lane, 66.3 to 60, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Claude Opus 4.8 or Muse Spark 1.2?
Claude Opus 4.8 leads the public agentic tasks lane, 63.1 to 61, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Claude Opus 4.8 or Muse Spark 1.2?
For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.00337 on Muse Spark 1.2; repository review costs $0.325 and $0.07525; the cache-heavy agent loop costs $1.35 and $0.0975. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Opus 4.8 or Muse Spark 1.2?
Both models list the same context window, 1M.
Related comparisons
Last updated September 18, 2026
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