Agentic
Not comparable- Granite 4.2 30B
- Not ranked
- Muse Spark 1.2
- 61.1
- Supported · #16/152
- Basis
- BenchAlign lane · 3 vs 2 public rows
- Reading
- Not comparable
Granite 4.2 30B vs Muse Spark 1.2
Updated September 10, 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 resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
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.
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
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Granite 4.2 30B is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Granite 4.2 30B is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Granite 4.2 30B does not fit this workload in one request. Granite 4.2 30B has no comparable published API token rate.
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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
12 Granite 4.2 30B only
2 Shared
6 Muse Spark 1.2 only
- Shared results
- 2
- Granite 4.2 30B only
- 12
- Muse Spark 1.2 only
- 6
- Like-for-like categories
- 0 / 8
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
Not comparable- Granite 4.2 30B
- Not ranked
- Muse Spark 1.2
- 60.0
- Supported · #21/151
- Basis
- BenchAlign lane · 6 vs 5 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Granite 4.2 30B
- 54.7
- Unranked · 2 rankable rows
- Muse Spark 1.2
- 75.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Granite 4.2 30B
- Not ranked
- Muse Spark 1.2
- 70.8
- Estimated · #10/183
- Basis
- BenchAlign lane · 2 vs 1 public rows
- Reading
- Not comparable
Math
Not comparable- Granite 4.2 30B
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Granite 4.2 30B
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Granite 4.2 30B
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Granite 4.2 30B
- Not ranked
- Muse Spark 1.2
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
| Category | Granite 4.2 30B | Muse Spark 1.2 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 61.1Supported · #16/152 | Not comparableBenchAlign lane · 3 vs 2 public rows | Not comparable |
| Coding | Not ranked | 60.0Supported · #21/151 | Not comparableBenchAlign lane · 6 vs 5 public rows | Not comparable |
| Reasoning | 54.7Unranked · 2 rankable rows | 75.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 70.8Estimated · #10/183 | Not comparableBenchAlign lane · 2 vs 1 public 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 | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 1 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
- Granite 4.2 30B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Muse Spark 1.2
- $0.00338
- Fits in one request
Granite 4.2 30B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Granite 4.2 30B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Muse Spark 1.2
- $0.07525
- Fits in one request
Granite 4.2 30B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Granite 4.2 30B
- Self-hosted; infrastructure cost varies
- Does not fit in one request
- Cached-input rate unavailable
- Muse Spark 1.2
- $0.0975
- Fits in one request
Granite 4.2 30B does not fit this workload in one request. Granite 4.2 30B 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.
SpecificationGranite 4.2 30BMuse Spark 1.2
Context window
Maximum documented context; output-token limits may be lower.
Granite 4.2 30B
Muse Spark 1.2
API model ID
Granite 4.2 30B
ibm-granite/granite-4.2-30b
IBM Granite 4.2 30B model cardMuse 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.
Granite 4.2 30B
No comparable hosted API rate
IBM Granite 4.2 30B model cardMuse Spark 1.2
$0.15 per 1M cached input tokens
Meta: Muse Spark 1.2 model pageDocumented inputs
Granite 4.2 30B
Not sourced
Muse Spark 1.2
Not sourced
Documented outputs
Granite 4.2 30B
Not sourced
Muse Spark 1.2
Not sourced
Provider availability
Granite 4.2 30B
Not sourced
Muse Spark 1.2
Not sourced
Reasoning profile
Granite 4.2 30B
Reasoning
Muse Spark 1.2
Reasoning
Weight access
Granite 4.2 30B
Open Weight
Muse Spark 1.2
Proprietary
License
Granite 4.2 30B
Open Weight
Muse Spark 1.2
Proprietary
Release date
Granite 4.2 30B
2026-08-25
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
- 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
- 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 evidence20 rows
Agentic
Terminal-Bench 2.1
Granite 4.2 30B29.2%SourceMuse Spark 1.282.9%SourceMuse Spark 1.2 leads this result
τ³-bench results
Granite 4.2 30B62.0%SourceMuse Spark 1.2—Not directly comparable
BFCL v4
Granite 4.2 30B61.4%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.1 (Vals)
Granite 4.2 30B—Muse Spark 1.269.7%SourceNot directly comparable
Coding
SWE Multilingual
Granite 4.2 30B41.9%SourceMuse Spark 1.2—Not directly comparable
SWE-bench Pro
Granite 4.2 30B33.3%SourceMuse Spark 1.2—Not directly comparable
SWE-bench Verified
Granite 4.2 30B57%SourceMuse Spark 1.2—Not directly comparable
Terminal-Bench 2.1
Granite 4.2 30B29.2%SourceMuse Spark 1.282.9%SourceMuse Spark 1.2 leads this result
LiveCodeBench v6
Granite 4.2 30B75.8%SourceMuse Spark 1.2—Not directly comparable
SciCode
Granite 4.2 30B38.8%SourceMuse Spark 1.2—Not directly comparable
DeepSWE
Granite 4.2 30B—Muse Spark 1.259.3%SourceNot directly comparable
VulcanBench v3
Granite 4.2 30B—Muse Spark 1.287.0%SourceNot directly comparable
FrontierSWE v2
Granite 4.2 30B—Muse Spark 1.212.0%SourceNot directly comparable
SWE-bench (Vals)
Granite 4.2 30B—Muse Spark 1.286.6%SourceNot directly comparable
Knowledge
Math
Instruction following
IFBench
Granite 4.2 30B77.2%SourceMuse Spark 1.2—Not directly comparable
Frequently asked questions
Which is better, Granite 4.2 30B or Muse Spark 1.2?
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, Granite 4.2 30B or Muse Spark 1.2?
Granite 4.2 30B is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Granite 4.2 30B or Muse Spark 1.2?
Granite 4.2 30B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Granite 4.2 30B 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, Granite 4.2 30B or Muse Spark 1.2?
Muse Spark 1.2 has the larger documented context window: 1M, compared with 128K.
Related comparisons
Last updated September 10, 2026
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