Coding
Like-for-like- Inkling
- 68.6
- Muse Spark
- 67.8
- Weighted basis
- 2 vs 2 rows
- Reading
- Inkling leads
Inkling vs Muse Spark
Updated August 29, 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, 71.02 versus 67.02, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
8 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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
Inkling
Inkling leads on the same 2 weighted benchmark rows.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Inkling
Inkling has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
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
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.
7 Inkling only
8 Shared
16 Muse Spark only
- Shared results
- 8
- Inkling only
- 7
- Muse Spark only
- 16
- Like-for-like categories
- 2 / 8
2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Multimodal
Like-for-like- Inkling
- 76.5
- Muse Spark
- 82.5
- Weighted basis
- 2 vs 2 rows
- Reading
- Muse Spark leads
Agentic
Directional only- Inkling
- 69.4
- Muse Spark
- 59.0
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Knowledge
Directional only- Inkling
- 51.6
- Muse Spark
- 50.4
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Reasoning
Not comparable- Inkling
- Not measured
- Muse Spark
- 42.5
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Math
Not comparable- Inkling
- 97.1
- Muse Spark
- 32.9
- Weighted basis
- 1 vs 2 rows
- Reading
- Not comparable
Multilingual
Not comparable- Inkling
- Not measured
- Muse Spark
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Inkling
- 79.8
- Muse Spark
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
| Category | Inkling | Muse Spark | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 68.6 | 67.8 | Like-for-like2 vs 2 rows | Inkling leads |
| Multimodal | 76.5 | 82.5 | Like-for-like2 vs 2 rows | Muse Spark leads |
| Agentic | 69.4 | 59.0 | Directional only2 vs 1 rows | Directional only |
| Knowledge | 51.6 | 50.4 | Directional only2 vs 1 rows | Directional only |
| Reasoning | Not measured | 42.5 | Not comparable0 vs 1 rows | Not comparable |
| Math | 97.1 | 32.9 | Not comparable1 vs 2 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | 79.8 | Not measured | Not comparable1 vs 0 rows | Not comparable |
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.
MMMU-Pro
Multimodal
Terminal-Bench 2.0
Agentic
CharXiv
Multimodal
HLE
Knowledge
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
- $0.00421
- 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
- $0.10754
- 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
- $0.159
- 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.
SpecificationInklingMuse Spark
Context window
Maximum documented context; output-token limits may be lower.
Inkling
1M
Muse Spark
262K
API model ID
Inkling
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
$0.374 per 1M cached input tokens
Muse Spark
No comparable hosted API rate
Documented inputs
Inkling
Not sourced
Muse Spark
Not sourced
Documented outputs
Inkling
Not sourced
Muse Spark
Not sourced
Provider availability
Inkling
Not sourced
Muse Spark
Not sourced
Reasoning profile
Inkling
Hybrid
Muse Spark
Reasoning
Weight access
Inkling
Open Weight
Muse Spark
Proprietary
License
Inkling
Open Weight
Muse Spark
Proprietary
Release date
Inkling
2026-07-15
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, 71.02 versus 67.02, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Inkling 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 evidence31 rows
Agentic
Terminal-Bench 2.0
Inkling63.8%SourceMuse Spark59%SourceInkling leads this result
BrowseComp
Inkling77.1%SourceMuse Spark—Not directly comparable
MCP Atlas
Inkling74.1%SourceMuse Spark—Not directly comparable
τ²-bench results
Inkling—Muse Spark91.5%SourceNot directly comparable
DeepSearchQA
Inkling—Muse Spark74.8%SourceNot directly comparable
CyberGym
Inkling—Muse Spark43.5%SourceNot directly comparable
Claw-Eval
Inkling—Muse Spark63.8%SourceNot directly comparable
Coding
SWE-bench Verified
Inkling77.6%SourceMuse Spark77.4%SourceInkling leads this result
SWE-bench Pro
Inkling54.3%SourceMuse Spark52.4%SourceInkling leads this result
Terminal-Bench 2.0
Inkling63.8%SourceMuse Spark—Not directly comparable
LiveCodeBench Pro
Inkling—Muse Spark80.0%SourceNot directly comparable
Vibe Code Bench
Inkling—Muse Spark19.67%SourceNot directly comparable
Reasoning
ARC-AGI-2
Inkling—Muse Spark42.5%SourceNot directly comparable
Knowledge
GPQA
Inkling87.9%SourceMuse Spark—Not directly comparable
GPQA-D
Inkling87.9%SourceMuse Spark89.5%SourceMuse Spark leads this result
HLE
Inkling46%SourceMuse Spark50.4%SourceMuse Spark leads this result
HLE w/o tools
Inkling30%SourceMuse Spark42.8%SourceMuse Spark leads this result
HealthBench Hard
Inkling—Muse Spark42.8%SourceNot directly comparable
MedXpertQA (Text)
Inkling—Muse Spark52.6%SourceNot directly comparable
Math
Multimodal
MMMU-Pro
Inkling73.5%SourceMuse Spark80.4%SourceMuse Spark leads this result
CharXiv
Inkling82%SourceMuse Spark86.4%SourceMuse Spark leads this result
CharXiv w/o tools
Inkling78.1%SourceMuse Spark—Not directly comparable
ERQA
Inkling—Muse Spark64.7%SourceNot directly comparable
SimpleVQA
Inkling—Muse Spark71.3%SourceNot directly comparable
ScreenSpot Pro
Inkling—Muse Spark84.1%SourceNot directly comparable
ZeroBench
Inkling—Muse Spark33.0%SourceNot directly comparable
MedXpertQA (MM)
Inkling—Muse Spark78.4%SourceNot directly comparable
Instruction following
IFBench
Inkling79.8%SourceMuse Spark—Not directly comparable
Frequently asked questions
Which is better, Inkling or Muse Spark?
Muse Spark has the higher public score estimate, 71.02 versus 67.02, 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 or Muse Spark?
Inkling leads the like-for-like coding comparison across 2 shared weighted benchmark rows.
Which is better for agentic tasks, Inkling or Muse Spark?
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Inkling 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 or Muse Spark?
Inkling has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated August 29, 2026
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