Agentic
Not comparable- Claude Opus 4.6
- 73.0
- Muse Spark 1.3
- Not measured
- Weighted basis
- 3 vs 0 rows
- Reading
- Not comparable
Claude Opus 4.6 vs Muse Spark 1.3
Updated September 2, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Chat turn cost
1K fresh input + 500 output tokens
Muse Spark 1.3
Muse Spark 1.3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Muse Spark 1.3
Muse Spark 1.3 has the lower estimated token cost for this stated workload. Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Muse Spark 1.3
Muse Spark 1.3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
31 Claude Opus 4.6 only
2 Shared
8 Muse Spark 1.3 only
- Shared results
- 2
- Claude Opus 4.6 only
- 31
- Muse Spark 1.3 only
- 8
- Like-for-like categories
- 0 / 8
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.
Coding
Not comparable- Claude Opus 4.6
- 68.1
- Muse Spark 1.3
- Not measured
- Weighted basis
- 3 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 4.6
- Not measured
- Muse Spark 1.3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Opus 4.6
- 69.1
- Muse Spark 1.3
- Not measured
- Weighted basis
- 4 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 4.6
- 36.3
- Muse Spark 1.3
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.6
- Not measured
- Muse Spark 1.3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.6
- 77.3
- Muse Spark 1.3
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.6
- Not measured
- Muse Spark 1.3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Claude Opus 4.6 | Muse Spark 1.3 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 73.0 | Not measured | Not comparable3 vs 0 rows | Not comparable |
| Coding | 68.1 | Not measured | Not comparable3 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 69.1 | Not measured | Not comparable4 vs 0 rows | Not comparable |
| Math | 36.3 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 77.3 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Instruction following | 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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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 4.6
- $0.0175
- Fits in one request
- Muse Spark 1.3
- $0.00338
- Fits in one request
Muse Spark 1.3 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 4.6
- $0.325
- Fits in one request
- Muse Spark 1.3
- $0.07525
- Fits in one request
Muse Spark 1.3 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 4.6
- $1.35
- Fits in one request
- Cached input priced at the published list-input rate
- Muse Spark 1.3
- $0.0975
- Fits in one request
Muse Spark 1.3 has the lower modeled cost
Claude Opus 4.6 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 4.6Muse Spark 1.3
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.6
1M
Muse Spark 1.3
API model ID
Claude Opus 4.6
Not sourced
Muse Spark 1.3
muse-spark-1.3
Meta Muse Spark 1.3 model pageCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 4.6
Not published
Muse Spark 1.3
$0.15 per 1M cached input tokens
Meta: Muse Spark 1.3 model pageDocumented inputs
Claude Opus 4.6
Not sourced
Muse Spark 1.3
text, image, video, document
Meta Muse Spark 1.3 model pageDocumented outputs
Claude Opus 4.6
Not sourced
Muse Spark 1.3
Provider availability
Claude Opus 4.6
Not sourced
Muse Spark 1.3
Generally Available · Meta Model API, Muse Code
Meta AI Research Muse Spark 1.3 launchReasoning profile
Claude Opus 4.6
Non-Reasoning
Muse Spark 1.3
Reasoning
Weight access
Claude Opus 4.6
Proprietary
Muse Spark 1.3
Proprietary
License
Claude Opus 4.6
Proprietary
Muse Spark 1.3
Proprietary
Release date
Claude Opus 4.6
2026-02-01
Muse Spark 1.3
2026-09-02
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
- 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 evidence41 rows
Agentic
Terminal-Bench 2.0
Claude Opus 4.665.4%SourceMuse Spark 1.3—Not directly comparable
BrowseComp
Claude Opus 4.683.7%SourceMuse Spark 1.3—Not directly comparable
OSWorld-Verified
Claude Opus 4.672.7%SourceMuse Spark 1.3—Not directly comparable
Claw-Eval
Claude Opus 4.670.4%SourceMuse Spark 1.3—Not directly comparable
DeepSearchQA
Claude Opus 4.673.7%SourceMuse Spark 1.389.4%SourceMuse Spark 1.3 leads this result
CyberGym
Claude Opus 4.666.6%SourceMuse Spark 1.3—Not directly comparable
Gert Labs
Claude Opus 4.661.85%SourceMuse Spark 1.3—Not directly comparable
ResearchClawBench
Claude Opus 4.619.9%SourceMuse Spark 1.3—Not directly comparable
JobBench
Claude Opus 4.636.7%SourceMuse Spark 1.364.9%SourceMuse Spark 1.3 leads this result
Terminal-Bench 2.1
Claude Opus 4.6—Muse Spark 1.388.8%SourceNot directly comparable
OSWorld 2.0
Claude Opus 4.6—Muse Spark 1.366.9%SourceNot directly comparable
AutomationBench
Claude Opus 4.6—Muse Spark 1.349.4%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Opus 4.680.8%SourceMuse Spark 1.3—Not directly comparable
SWE-bench Verified*
Claude Opus 4.675.6%SourceMuse Spark 1.3—Not directly comparable
LiveCodeBench Pro
Claude Opus 4.670.7%SourceMuse Spark 1.3—Not directly comparable
SWE-bench Pro
Claude Opus 4.653.4%SourceMuse Spark 1.3—Not directly comparable
SWE-Rebench
Claude Opus 4.665.3%SourceMuse Spark 1.3—Not directly comparable
React Native Evals
Claude Opus 4.684.1%SourceMuse Spark 1.3—Not directly comparable
Vibe Code Bench
Claude Opus 4.657.57%SourceMuse Spark 1.3—Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.626.9%SourceMuse Spark 1.3—Not directly comparable
Terminal-Bench 2.1
Claude Opus 4.6—Muse Spark 1.388.8%SourceNot directly comparable
deepSwe
Claude Opus 4.6—Muse Spark 1.375.4%SourceNot directly comparable
SWE-Atlas Codebase QnA
Claude Opus 4.6—Muse Spark 1.359.4%SourceNot directly comparable
Reasoning
Knowledge
GPQA
Claude Opus 4.691.3%SourceMuse Spark 1.3—Not directly comparable
GPQA-D
Claude Opus 4.689.2%SourceMuse Spark 1.3—Not directly comparable
SuperGPQA
Claude Opus 4.695%SourceMuse Spark 1.3—Not directly comparable
MMLU-Pro
Claude Opus 4.682%SourceMuse Spark 1.3—Not directly comparable
MMLU-Pro (Arcee)
Claude Opus 4.689.1%SourceMuse Spark 1.3—Not directly comparable
HLE
Claude Opus 4.653%SourceMuse Spark 1.3—Not directly comparable
HLE w/o tools
Claude Opus 4.640%SourceMuse Spark 1.3—Not directly comparable
HealthBench Hard
Claude Opus 4.614.8%SourceMuse Spark 1.3—Not directly comparable
MedXpertQA (Text)
Claude Opus 4.652.1%SourceMuse Spark 1.3—Not directly comparable
Math
Multimodal
MMMU-Pro
Claude Opus 4.677.3%SourceMuse Spark 1.3—Not directly comparable
ERQA
Claude Opus 4.651.6%SourceMuse Spark 1.3—Not directly comparable
ScreenSpot Pro
Claude Opus 4.683.1%SourceMuse Spark 1.3—Not directly comparable
MedXpertQA (MM)
Claude Opus 4.664.8%SourceMuse Spark 1.3—Not directly comparable
Frequently asked questions
Which is better, Claude Opus 4.6 or Muse Spark 1.3?
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, Claude Opus 4.6 or Muse Spark 1.3?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Claude Opus 4.6 or Muse Spark 1.3?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Claude Opus 4.6 or Muse Spark 1.3?
For the stated presets, chat costs $0.0175 on Claude Opus 4.6 and $0.00337 on Muse Spark 1.3; repository review costs $0.325 and $0.07525; the cache-heavy agent loop costs $1.35 and $0.0975. Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Opus 4.6 or Muse Spark 1.3?
Both models list the same context window, 1M.
Related comparisons
Last updated September 2, 2026
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