Agentic
Like-for-like- Muse Spark 1.1
- 60.0
- Supported · #21/154
- Muse Spark 1.2
- 61.0
- Supported · #16/154
- Basis
- BenchAlign lane · 14 vs 2 public rows
- Reading
- Muse Spark 1.2 leads · intervals overlap
Muse Spark 1.1 vs Muse Spark 1.2
Decision reading
Muse Spark 1.2 has the higher public score estimate, 70.28 versus 70.18, 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 cannot separate these two. Price, access, and your workload decide. 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
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
Muse Spark 1.2
Muse Spark 1.2 leads on the public coding lane, 60 to 59.5, 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 60, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Show secondary and unsupported calls
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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.
59.5Muse Spark 1.160.0Muse 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.
23 Muse Spark 1.1 only
3 Shared
5 Muse Spark 1.2 only
- Shared results
- 3
- Muse Spark 1.1 only
- 23
- 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- Muse Spark 1.1
- 59.5
- Supported · #23/154
- 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 1.1
- 70.6
- Supported · #11/184
- 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 1.1
- 74.4
- Unranked · 3 rankable rows
- Muse Spark 1.2
- 75.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Muse Spark 1.1
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Muse Spark 1.1
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Muse Spark 1.1
- 77.3
- Unranked · 2 rankable rows
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Muse Spark 1.1
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Muse Spark 1.1 | Muse Spark 1.2 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 60.0Supported · #21/154 | 61.0Supported · #16/154 | Like-for-likeBenchAlign lane · 14 vs 2 public rows | Muse Spark 1.2 leads · intervals overlap |
| Coding | 59.5Supported · #23/154 | 60.0Supported · #21/154 | Like-for-likeBenchAlign lane · 4 vs 5 public rows | Muse Spark 1.2 leads · intervals overlap |
| Knowledge | 70.6Supported · #11/184 | 70.7Estimated · #10/184 | Directional onlyBenchAlign lane · 5 vs 1 public rows | Directional only |
| Reasoning | 74.4Unranked · 3 rankable rows | 75.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 77.3Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 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
Muse Spark 1.1: 88.7%Muse Spark 1.2: 88.3%Normalized gap 0.4Muse Spark 1.1 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
- Muse Spark 1.1
- API rate not published
- Fits in one request
- Muse Spark 1.2
- $0.00338
- Fits in one request
Muse Spark 1.1 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Muse Spark 1.1
- API rate not published
- Fits in one request
- Muse Spark 1.2
- $0.07525
- Fits in one request
Muse Spark 1.1 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Muse Spark 1.1
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Muse Spark 1.2
- $0.0975
- Fits in one request
Muse Spark 1.1 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 Spark 1.1Muse Spark 1.2
Context window
Maximum documented context; output-token limits may be lower.
Muse Spark 1.1
1M
Muse Spark 1.2
API model ID
Muse Spark 1.1
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 1.1
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 1.1
Not sourced
Muse Spark 1.2
Not sourced
Documented outputs
Muse Spark 1.1
Not sourced
Muse Spark 1.2
Not sourced
Provider availability
Muse Spark 1.1
Not sourced
Muse Spark 1.2
Not sourced
Reasoning profile
Muse Spark 1.1
Reasoning
Muse Spark 1.2
Reasoning
Weight access
Muse Spark 1.1
Proprietary
Muse Spark 1.2
Proprietary
License
Muse Spark 1.1
Proprietary
Muse Spark 1.2
Proprietary
Release date
Muse Spark 1.1
2026-07-09
Muse Spark 1.2
2026-08-05
If you are considering the documented upgrade path
- Deployment change
- Both entries list Meta as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- Muse Spark 1.2 has the higher public score estimate, 70.28 versus 70.18, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- 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 evidence31 rows
Agentic
Terminal-Bench 2.0
Muse Spark 1.180%SourceMuse Spark 1.2—Not directly comparable
MCP Atlas
Muse Spark 1.188.1%SourceMuse Spark 1.2—Not directly comparable
Toolathlon
Muse Spark 1.175.6%SourceMuse Spark 1.2—Not directly comparable
OSWorld-Verified
Muse Spark 1.180.8%SourceMuse Spark 1.2—Not directly comparable
WebArena-Verified
Muse Spark 1.169%SourceMuse Spark 1.2—Not directly comparable
DeepSearchQA
Muse Spark 1.184.9%SourceMuse Spark 1.2—Not directly comparable
CyberGym
Muse Spark 1.159.0%SourceMuse Spark 1.2—Not directly comparable
Finance Agent v2
Muse Spark 1.157.2%SourceMuse Spark 1.2—Not directly comparable
deepSwe
Muse Spark 1.153.3%SourceMuse Spark 1.2—Not directly comparable
OSWorld 2.0
Muse Spark 1.114.2%SourceMuse Spark 1.2—Not directly comparable
JobBench
Muse Spark 1.154.7%SourceMuse Spark 1.2—Not directly comparable
Cybench
Muse Spark 1.192.9%SourceMuse Spark 1.2—Not directly comparable
ExploitGym
Muse Spark 1.10.8%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.1 (Vals)
Muse Spark 1.169.3%SourceMuse Spark 1.269.7%SourceMuse Spark 1.2 leads this result
Terminal-Bench 2.1
Muse Spark 1.1—Muse Spark 1.282.9%SourceNot directly comparable
Coding
Terminal-Bench 2.0
Muse Spark 1.180.0%SourceMuse Spark 1.2—Not directly comparable
SWE-bench Pro
Muse Spark 1.161.5%SourceMuse Spark 1.2—Not directly comparable
LiveCodeBench (Vals)
Muse Spark 1.185.9%SourceMuse Spark 1.2—Not directly comparable
SWE-bench (Vals)
Muse Spark 1.182.0%SourceMuse Spark 1.286.6%SourceMuse Spark 1.2 leads this result
Terminal-Bench 2.1
Muse Spark 1.1—Muse Spark 1.282.9%SourceNot directly comparable
DeepSWE
Muse Spark 1.1—Muse Spark 1.259.3%SourceNot directly comparable
VulcanBench v3
Muse Spark 1.1—Muse Spark 1.287.0%SourceNot directly comparable
FrontierSWE v2
Muse Spark 1.1—Muse Spark 1.212.0%SourceNot directly comparable
Reasoning
MRCR 1M
Muse Spark 1.154.1%SourceMuse Spark 1.2—Not directly comparable
Knowledge
HLE
Muse Spark 1.162.1%SourceMuse Spark 1.2—Not directly comparable
HLE w/o tools
Muse Spark 1.152.2%SourceMuse Spark 1.2—Not directly comparable
HealthBench Professional
Muse Spark 1.159.3%SourceMuse Spark 1.2—Not directly comparable
GPQA Diamond (Vals)
Muse Spark 1.191.2%SourceMuse Spark 1.2—Not directly comparable
MMLU-Pro (Vals)
Muse Spark 1.188.7%SourceMuse Spark 1.288.3%SourceMuse Spark 1.1 leads this result
Multimodal
Questions
Which is better, Muse Spark 1.1 or Muse Spark 1.2?
Muse Spark 1.2 has the higher public score estimate, 70.28 versus 70.18, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Muse Spark 1.1 or Muse Spark 1.2?
Muse Spark 1.2 leads the public coding lane, 60 to 59.5, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Muse Spark 1.1 or Muse Spark 1.2?
Muse Spark 1.2 leads the public agentic tasks lane, 61 to 60, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Muse Spark 1.1 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 1.1 or Muse Spark 1.2?
Both models list the same context window, 1M.
Related comparisons
Last updated September 18, 2026
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