Agentic
Like-for-like- Muse Spark
- 58.2
- Supported · #32/154
- Muse Spark 1.2
- 61.0
- Supported · #16/154
- Basis
- BenchAlign lane · 5 vs 2 public rows
- Reading
- Muse Spark 1.2 leads · intervals overlap
Muse Spark vs Muse Spark 1.2
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 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 Muse Spark 1.2 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty. This is a same-family comparison, so migration details appear when the source data supports them.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
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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
Muse Spark 1.2
Muse Spark 1.2 leads on the public coding lane, 60 to 58.8, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Muse Spark 1.2
Muse Spark 1.2 leads on the public agentic lane, 61 to 58.2, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Muse Spark 1.2
Muse Spark 1.2 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
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.
58.8Muse Spark60.0Muse Spark 1.2
Like-for-like · BenchAlign
Muse Spark 1.2 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.
24 Muse Spark only
8 Muse Spark 1.2 only
- Shared results
- 0
- Muse Spark only
- 24
- Muse Spark 1.2 only
- 8
- 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- Muse Spark
- 58.8
- Supported · #26/154
- Muse Spark 1.2
- 60.0
- Supported · #21/154
- Basis
- BenchAlign lane · 4 vs 5 public rows
- Reading
- Muse Spark 1.2 leads · intervals overlap
Knowledge
Directional only- Muse Spark
- 65.3
- Supported · #24/184
- Muse Spark 1.2
- 70.7
- Estimated · #10/184
- Basis
- BenchAlign lane · 5 vs 1 public rows
- Reading
- Directional only
Reasoning
Not comparable- Muse Spark
- 45.1
- Unranked · 3 rankable rows
- Muse Spark 1.2
- 75.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Muse Spark
- 55.1
- Unranked · 2 rankable rows
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Muse Spark
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Muse Spark
- 77.5
- #13/48
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Muse Spark
- 91.9
- #8/124
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Muse Spark | Muse Spark 1.2 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 58.2Supported · #32/154 | 61.0Supported · #16/154 | Like-for-likeBenchAlign lane · 5 vs 2 public rows | Muse Spark 1.2 leads · intervals overlap |
| Coding | 58.8Supported · #26/154 | 60.0Supported · #21/154 | Like-for-likeBenchAlign lane · 4 vs 5 public rows | Muse Spark 1.2 leads · intervals overlap |
| Knowledge | 65.3Supported · #24/184 | 70.7Estimated · #10/184 | Directional onlyBenchAlign lane · 5 vs 1 public rows | Directional only |
| Reasoning | 45.1Unranked · 3 rankable rows | 75.3Unranked · 2 rankable rows | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Math | 55.1Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 77.5#13/48 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Instruction following | 91.9#8/124 | 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.
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
- Muse Spark
- API rate not published
- Fits in one request
- Muse Spark 1.2
- $0.00338
- Fits in one request
Muse Spark has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Muse Spark
- API rate not published
- Fits in one request
- Muse Spark 1.2
- $0.07525
- 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
- Muse Spark
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Muse Spark 1.2
- $0.0975
- Fits in one request
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.
SpecificationMuse SparkMuse Spark 1.2
Context window
Maximum documented context; output-token limits may be lower.
Muse Spark
262K
Muse Spark 1.2
API model ID
Muse Spark
Not sourced
Muse 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.
Muse Spark
No comparable hosted API rate
Muse Spark 1.2
$0.15 per 1M cached input tokens
Meta: Muse Spark 1.2 model pageDocumented inputs
Muse Spark
Not sourced
Muse Spark 1.2
Not sourced
Documented outputs
Muse Spark
Not sourced
Muse Spark 1.2
Not sourced
Provider availability
Muse Spark
Not sourced
Muse Spark 1.2
Not sourced
Reasoning profile
Muse Spark
Reasoning
Muse Spark 1.2
Reasoning
Weight access
Muse Spark
Proprietary
Muse Spark 1.2
Proprietary
License
Muse Spark
Proprietary
Muse Spark 1.2
Proprietary
Release date
Muse Spark
2026-04-08
Muse Spark 1.2
2026-08-05
If you are choosing between sibling variants
- Deployment change
- Both entries list Meta as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Muse Spark 1.2 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 evidence32 rows
Agentic
Terminal-Bench 2.0
Muse Spark59%SourceMuse Spark 1.2—Not directly comparable
τ²-bench results
Muse Spark91.5%SourceMuse Spark 1.2—Not directly comparable
DeepSearchQA
Muse Spark74.8%SourceMuse Spark 1.2—Not directly comparable
CyberGym
Muse Spark43.5%SourceMuse Spark 1.2—Not directly comparable
Claw-Eval
Muse Spark63.8%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.1
Muse Spark—Muse Spark 1.282.9%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Muse Spark—Muse Spark 1.269.7%SourceNot directly comparable
Coding
SWE-bench Verified
Muse Spark77.4%SourceMuse Spark 1.2—Not directly comparable
SWE-bench Pro
Muse Spark52.4%SourceMuse Spark 1.2—Not directly comparable
LiveCodeBench Pro
Muse Spark80.0%SourceMuse Spark 1.2—Not directly comparable
Vibe Code Bench
Muse Spark19.67%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.1
Muse Spark—Muse Spark 1.282.9%SourceNot directly comparable
DeepSWE
Muse Spark—Muse Spark 1.259.3%SourceNot directly comparable
VulcanBench v3
Muse Spark—Muse Spark 1.287.0%SourceNot directly comparable
FrontierSWE v2
Muse Spark—Muse Spark 1.212.0%SourceNot directly comparable
SWE-bench (Vals)
Muse Spark—Muse Spark 1.286.6%SourceNot directly comparable
Reasoning
ARC-AGI-2
Muse Spark42.5%SourceMuse Spark 1.2—Not directly comparable
Knowledge
GPQA-D
Muse Spark89.5%SourceMuse Spark 1.2—Not directly comparable
HLE
Muse Spark50.4%SourceMuse Spark 1.2—Not directly comparable
HLE w/o tools
Muse Spark42.8%SourceMuse Spark 1.2—Not directly comparable
HealthBench Hard
Muse Spark42.8%SourceMuse Spark 1.2—Not directly comparable
MedXpertQA (Text)
Muse Spark52.6%SourceMuse Spark 1.2—Not directly comparable
MMLU-Pro (Vals)
Muse Spark—Muse Spark 1.288.3%SourceNot directly comparable
Math
Multimodal
CharXiv
Muse Spark86.4%SourceMuse Spark 1.2—Not directly comparable
MMMU-Pro
Muse Spark80.4%SourceMuse Spark 1.2—Not directly comparable
ERQA
Muse Spark64.7%SourceMuse Spark 1.2—Not directly comparable
SimpleVQA
Muse Spark71.3%SourceMuse Spark 1.2—Not directly comparable
ScreenSpot Pro
Muse Spark84.1%SourceMuse Spark 1.2—Not directly comparable
ZeroBench
Muse Spark33.0%SourceMuse Spark 1.2—Not directly comparable
MedXpertQA (MM)
Muse Spark78.4%SourceMuse Spark 1.2—Not directly comparable
Questions
Which is better, Muse Spark or Muse Spark 1.2?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Muse Spark or Muse Spark 1.2?
Muse Spark 1.2 leads the public coding lane, 60 to 58.8, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Muse Spark or Muse Spark 1.2?
Muse Spark 1.2 leads the public agentic tasks lane, 61 to 58.2, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Muse Spark or Muse Spark 1.2?
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 Spark or Muse Spark 1.2?
Muse Spark 1.2 has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 18, 2026
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