Agentic
Like-for-like- Claude Haiku 4.5
- 27.0
- Supported · #146/154
- Muse Spark 1.2
- 61.0
- Supported · #16/154
- Basis
- BenchAlign lane · 2 vs 2 public rows
- Reading
- Muse Spark 1.2 leads
Claude Haiku 4.5 vs Muse Spark 1.2
Decision reading
Muse Spark 1.2 has the higher public score estimate, 70.28 versus 52.89, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
4 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.
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 27.4, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
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 27, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
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
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
Repository review cost
50K fresh input + 3K output tokens
Claude Haiku 4.5
Claude Haiku 4.5 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
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Haiku 4.5 does not fit this workload in one request.
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.
27.4Claude Haiku 4.560.0Muse Spark 1.2
Like-for-like · BenchAlign
Muse Spark 1.2 leads the like-for-like coding row.
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.
6 Claude Haiku 4.5 only
4 Shared
4 Muse Spark 1.2 only
- Shared results
- 4
- Claude Haiku 4.5 only
- 6
- Muse Spark 1.2 only
- 4
- 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 Haiku 4.5
- 27.4
- Supported · #147/154
- Muse Spark 1.2
- 60.0
- Supported · #21/154
- Basis
- BenchAlign lane · 4 vs 5 public rows
- Reading
- Muse Spark 1.2 leads
Knowledge
Directional only- Claude Haiku 4.5
- 44.5
- Estimated · #117/184
- Muse Spark 1.2
- 70.7
- Estimated · #10/184
- Basis
- BenchAlign lane · 2 vs 1 public rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Haiku 4.5
- Not ranked
- Muse Spark 1.2
- 75.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Haiku 4.5
- 28.8
- Unranked · 2 rankable rows
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Haiku 4.5
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Haiku 4.5
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Haiku 4.5
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Haiku 4.5 | Muse Spark 1.2 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 27.0Supported · #146/154 | 61.0Supported · #16/154 | Like-for-likeBenchAlign lane · 2 vs 2 public rows | Muse Spark 1.2 leads |
| Coding | 27.4Supported · #147/154 | 60.0Supported · #21/154 | Like-for-likeBenchAlign lane · 4 vs 5 public rows | Muse Spark 1.2 leads |
| Knowledge | 44.5Estimated · #117/184 | 70.7Estimated · #10/184 | Directional onlyBenchAlign lane · 2 vs 1 public rows | Directional only |
| Reasoning | Not ranked | 75.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 28.8Unranked · 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 | Not ranked | Not ranked | Not comparableProvisional lane · 0 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
Claude Haiku 4.5: 78.7%Muse Spark 1.2: 88.3%Normalized gap 9.6Claude Haiku 4.5 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 Haiku 4.5
- $0.0035
- 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 Haiku 4.5
- $0.065
- Fits in one request
- Muse Spark 1.2
- $0.07525
- Fits in one request
Claude Haiku 4.5 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 Haiku 4.5
- $0.09
- Does not fit in one request
- Muse Spark 1.2
- $0.0975
- Fits in one request
Claude Haiku 4.5 does not fit this workload in one request.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Haiku 4.5Muse Spark 1.2
Context window
Maximum documented context; output-token limits may be lower.
Claude Haiku 4.5
Muse Spark 1.2
API model ID
Claude Haiku 4.5
claude-haiku-4-5-20251001
Claude API pricingMuse 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 Haiku 4.5
$0.1 per 1M cached input tokens
Claude API pricingMuse Spark 1.2
$0.15 per 1M cached input tokens
Meta: Muse Spark 1.2 model pageDocumented inputs
Claude Haiku 4.5
Not sourced
Muse Spark 1.2
Not sourced
Documented outputs
Claude Haiku 4.5
Not sourced
Muse Spark 1.2
Not sourced
Provider availability
Claude Haiku 4.5
Not sourced
Muse Spark 1.2
Not sourced
Reasoning profile
Claude Haiku 4.5
Non-Reasoning
Muse Spark 1.2
Reasoning
Weight access
Claude Haiku 4.5
Proprietary
Muse Spark 1.2
Proprietary
License
Claude Haiku 4.5
Proprietary
Muse Spark 1.2
Proprietary
Release date
Claude Haiku 4.5
2025-10-15
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
- Muse Spark 1.2 has the higher public score estimate, 70.28 versus 52.89, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.065 vs $0.07525. Cache-heavy agent loop: $0.09 vs $0.0975.
- 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 evidence14 rows
Agentic
Coding
SWE-bench Verified
Claude Haiku 4.573.3%SourceMuse Spark 1.2—Not directly comparable
VulcanBench v3
Claude Haiku 4.576.2%SourceMuse Spark 1.287.0%SourceMuse Spark 1.2 leads this result
LiveCodeBench (Vals)
Claude Haiku 4.541.2%SourceMuse Spark 1.2—Not directly comparable
SWE-bench (Vals)
Claude Haiku 4.566.6%SourceMuse Spark 1.286.6%SourceMuse Spark 1.2 leads this result
Terminal-Bench 2.1
Claude Haiku 4.5—Muse Spark 1.282.9%SourceNot directly comparable
DeepSWE
Claude Haiku 4.5—Muse Spark 1.259.3%SourceNot directly comparable
FrontierSWE v2
Claude Haiku 4.5—Muse Spark 1.212.0%SourceNot directly comparable
Knowledge
Math
Questions
Which is better, Claude Haiku 4.5 or Muse Spark 1.2?
Muse Spark 1.2 has the higher public score estimate, 70.28 versus 52.89, 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 Haiku 4.5 or Muse Spark 1.2?
Muse Spark 1.2 leads the public coding lane, 60 to 27.4, with Supported evidence for both models and non-overlapping 90% intervals.
Which is better for agentic tasks, Claude Haiku 4.5 or Muse Spark 1.2?
Muse Spark 1.2 leads the public agentic tasks lane, 61 to 27, with Supported evidence for both models and non-overlapping 90% intervals.
Which costs less, Claude Haiku 4.5 or Muse Spark 1.2?
For the stated presets, chat costs $0.0035 on Claude Haiku 4.5 and $0.00337 on Muse Spark 1.2; repository review costs $0.065 and $0.07525; the cache-heavy agent loop costs $0.09 and $0.0975. Claude Haiku 4.5 does not fit this workload in one request.
Which has the larger context window, Claude Haiku 4.5 or Muse Spark 1.2?
Muse Spark 1.2 has the larger documented context window: 1M, compared with 200K.
Related comparisons
Last updated September 18, 2026
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