Agentic
Like-for-like- Inkling-Small
- 36.9
- Supported · #128/152
- Muse Spark
- 56.1
- Supported · #34/152
- Basis
- BenchAlign lane · 5 vs 5 public rows
- Reading
- Muse Spark leads · intervals overlap
Inkling-Small vs Muse Spark
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Muse Spark has the higher public score estimate, 67.69 versus 59.25, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
9 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.
Coding work
Code generation, repair, and software-engineering tasks
Muse Spark
Muse Spark leads on the public coding lane, 59 to 43.8, 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
Muse Spark leads on the public agentic lane, 56.1 to 36.9, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Inkling-Small
Inkling-Small 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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
16 Inkling-Small only
9 Shared
15 Muse Spark only
- Shared results
- 9
- Inkling-Small only
- 16
- Muse Spark only
- 15
- Like-for-like categories
- 4 / 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- Inkling-Small
- 43.8
- Supported · #97/151
- Muse Spark
- 59.0
- Supported · #25/151
- Basis
- BenchAlign lane · 6 vs 4 public rows
- Reading
- Muse Spark leads · intervals overlap
Knowledge
Like-for-like- Inkling-Small
- 56.5
- Supported · #46/183
- Muse Spark
- 65.4
- Supported · #24/183
- Basis
- BenchAlign lane · 6 vs 5 public rows
- Reading
- Muse Spark leads · intervals overlap
Multimodal
Like-for-like- Inkling-Small
- 48.8
- #39/48
- Muse Spark
- 77.5
- #14/48
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Muse Spark leads
Instruction following
Directional only- Inkling-Small
- 89.6
- #25/123
- Muse Spark
- 93.2
- #8/123
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Inkling-Small
- 42.7
- Unranked · 3 rankable rows
- Muse Spark
- 45.1
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- Inkling-Small
- 76.9
- Unranked · 2 rankable rows
- Muse Spark
- 55.3
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Inkling-Small
- Not ranked
- Muse Spark
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Inkling-Small | Muse Spark | Basis | Reading |
|---|---|---|---|---|
| Agentic | 36.9Supported · #128/152 | 56.1Supported · #34/152 | Like-for-likeBenchAlign lane · 5 vs 5 public rows | Muse Spark leads · intervals overlap |
| Coding | 43.8Supported · #97/151 | 59.0Supported · #25/151 | Like-for-likeBenchAlign lane · 6 vs 4 public rows | Muse Spark leads · intervals overlap |
| Knowledge | 56.5Supported · #46/183 | 65.4Supported · #24/183 | Like-for-likeBenchAlign lane · 6 vs 5 public rows | Muse Spark leads · intervals overlap |
| Multimodal | 48.8#39/48 | 77.5#14/48 | Like-for-likeProvisional lane · 2 vs 2 weighted rows | Muse Spark leads |
| Instruction following | 89.6#25/123 | 93.2#8/123 | Directional onlyProvisional lane · 1 vs 0 weighted rows | Directional only |
| Reasoning | 42.7Unranked · 3 rankable rows | 45.1Unranked · 3 rankable rows | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
| Math | 76.9Unranked · 2 rankable rows | 55.3Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 2 weighted rows | Not comparable |
| Multilingual | 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.
HLE w/o tools
Knowledge
MMMU-Pro
Multimodal
Terminal-Bench 2.0
Agentic
CharXiv
Multimodal
SWE-bench Pro
Coding
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
- Inkling-Small
- $0.0013
- Fits in one request
- Muse Spark
- API rate not published
- Fits in one request
Muse Spark has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Inkling-Small
- $0.03332
- Fits in one request
- Muse Spark
- API rate not published
- 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
- Inkling-Small
- $0.0492
- Fits in one request
- Muse Spark
- API rate not published
- Fits in one request
- Cached-input rate unavailable
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.
SpecificationInkling-SmallMuse Spark
Context window
Maximum documented context; output-token limits may be lower.
Inkling-Small
1M
Muse Spark
262K
API model ID
Inkling-Small
Not sourced
Muse Spark
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Inkling-Small
$0.116 per 1M cached input tokens
Muse Spark
No comparable hosted API rate
Documented inputs
Inkling-Small
Not sourced
Muse Spark
Not sourced
Documented outputs
Inkling-Small
Not sourced
Muse Spark
Not sourced
Provider availability
Inkling-Small
Not sourced
Muse Spark
Not sourced
Reasoning profile
Inkling-Small
Hybrid
Muse Spark
Reasoning
Weight access
Inkling-Small
Open Weight
Muse Spark
Proprietary
License
Inkling-Small
Open Weight
Muse Spark
Proprietary
Release date
Inkling-Small
2026-07-30
Muse Spark
2026-04-08
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 has the higher public score estimate, 67.69 versus 59.25, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Inkling-Small 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 evidence40 rows
Agentic
Terminal-Bench 2.0
Inkling-Small64.7%SourceMuse Spark59%SourceInkling-Small leads this result
BrowseComp
Inkling-Small77.4%SourceMuse Spark—Not directly comparable
MCP Atlas
Inkling-Small79.6%SourceMuse Spark—Not directly comparable
Toolathlon-Verified
Inkling-Small54.4%SourceMuse Spark—Not directly comparable
Terminal-Bench 2.1 (Vals)
Inkling-Small55.1%SourceMuse Spark—Not directly comparable
τ²-bench results
Inkling-Small—Muse Spark91.5%SourceNot directly comparable
DeepSearchQA
Inkling-Small—Muse Spark74.8%SourceNot directly comparable
CyberGym
Inkling-Small—Muse Spark43.5%SourceNot directly comparable
Claw-Eval
Inkling-Small—Muse Spark63.8%SourceNot directly comparable
Coding
SWE-bench Verified
Inkling-Small80.2%SourceMuse Spark77.4%SourceInkling-Small leads this result
SWE-bench Pro
Inkling-Small55.9%SourceMuse Spark52.4%SourceInkling-Small leads this result
Terminal-Bench 2.0
Inkling-Small64.7%SourceMuse Spark—Not directly comparable
SciCode
Inkling-Small48.7%SourceMuse Spark—Not directly comparable
LiveCodeBench (Vals)
Inkling-Small85.9%SourceMuse Spark—Not directly comparable
SWE-bench (Vals)
Inkling-Small82.2%SourceMuse Spark—Not directly comparable
LiveCodeBench Pro
Inkling-Small—Muse Spark80.0%SourceNot directly comparable
Vibe Code Bench
Inkling-Small—Muse Spark19.67%SourceNot directly comparable
Reasoning
Knowledge
GPQA
Inkling-Small89.5%SourceMuse Spark—Not directly comparable
GPQA-D
Inkling-Small89.5%SourceMuse Spark89.5%SourceTie
HLE
Inkling-Small47.8%SourceMuse Spark50.4%SourceMuse Spark leads this result
HLE w/o tools
Inkling-Small31.6%SourceMuse Spark42.8%SourceMuse Spark leads this result
GPQA Diamond (Vals)
Inkling-Small83.6%SourceMuse Spark—Not directly comparable
MMLU-Pro (Vals)
Inkling-Small85.6%SourceMuse Spark—Not directly comparable
HealthBench Hard
Inkling-Small—Muse Spark42.8%SourceNot directly comparable
MedXpertQA (Text)
Inkling-Small—Muse Spark52.6%SourceNot directly comparable
Math
AIME26
Inkling-Small95.5%SourceMuse Spark—Not directly comparable
HMMT Feb 2026
Inkling-Small90.2%SourceMuse Spark—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Inkling-Small—Muse Spark39.000%SourceNot directly comparable
FrontierMath v2 (Tier 4)
Inkling-Small—Muse Spark14.600%SourceNot directly comparable
Multimodal
MMMU-Pro
Inkling-Small74%SourceMuse Spark80.4%SourceMuse Spark leads this result
CharXiv
Inkling-Small81.3%SourceMuse Spark86.4%SourceMuse Spark leads this result
CharXiv w/o tools
Inkling-Small77.4%SourceMuse Spark—Not directly comparable
ERQA
Inkling-Small—Muse Spark64.7%SourceNot directly comparable
SimpleVQA
Inkling-Small—Muse Spark71.3%SourceNot directly comparable
ScreenSpot Pro
Inkling-Small—Muse Spark84.1%SourceNot directly comparable
ZeroBench
Inkling-Small—Muse Spark33.0%SourceNot directly comparable
MedXpertQA (MM)
Inkling-Small—Muse Spark78.4%SourceNot directly comparable
Instruction following
IFBench
Inkling-Small82.2%SourceMuse Spark—Not directly comparable
Frequently asked questions
Which is better, Inkling-Small or Muse Spark?
Muse Spark has the higher public score estimate, 67.69 versus 59.25, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Inkling-Small or Muse Spark?
Muse Spark leads the public coding lane, 59 to 43.8, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Inkling-Small or Muse Spark?
Muse Spark leads the public agentic tasks lane, 56.1 to 36.9, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Inkling-Small or Muse Spark?
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, Inkling-Small or Muse Spark?
Inkling-Small has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 10, 2026
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