Agentic
Not comparable- Laguna S 2.1
- 70.2
- Muse Spark 1.2
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Model comparison
Laguna S 2.1 vs Muse Spark 1.2
Updated August 5, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
1 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.
Chat turn cost
1K fresh input + 500 output tokens
Laguna S 2.1
Laguna S 2.1 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
Laguna S 2.1
Laguna S 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Laguna S 2.1
Laguna S 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
5 Laguna S 2.1 only
1 Shared
2 Muse Spark 1.2 only
- Shared results
- 1
- Laguna S 2.1 only
- 5
- Muse Spark 1.2 only
- 2
- Like-for-like categories
- 0 / 8
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.
Coding
Not comparable- Laguna S 2.1
- 59.4
- Muse Spark 1.2
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Laguna S 2.1
- Not measured
- Muse Spark 1.2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Laguna S 2.1
- Not measured
- Muse Spark 1.2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Laguna S 2.1
- Not measured
- Muse Spark 1.2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Laguna S 2.1
- Not measured
- Muse Spark 1.2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Laguna S 2.1
- Not measured
- Muse Spark 1.2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Laguna S 2.1
- Not measured
- Muse Spark 1.2
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Laguna S 2.1 | Muse Spark 1.2 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 70.2 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Coding | 59.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 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.
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
- Laguna S 2.1
- $0.0002
- Fits in one request
- Muse Spark 1.2
- $0.00338
- Fits in one request
Laguna S 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Laguna S 2.1
- $0.0056
- Fits in one request
- Muse Spark 1.2
- $0.07525
- Fits in one request
Laguna S 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Laguna S 2.1
- $0.006
- Fits in one request
- Muse Spark 1.2
- $0.0975
- Fits in one request
Laguna S 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationLaguna S 2.1Muse Spark 1.2
Context window
Maximum documented context; output-token limits may be lower.
Laguna S 2.1
1M
Muse Spark 1.2
API model ID
Laguna S 2.1
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.
Laguna S 2.1
$0.01 per 1M cached input tokens
Muse Spark 1.2
$0.15 per 1M cached input tokens
Meta: Muse Spark 1.2 model pageDocumented inputs
Laguna S 2.1
Not sourced
Muse Spark 1.2
Not sourced
Documented outputs
Laguna S 2.1
Not sourced
Muse Spark 1.2
Not sourced
Provider availability
Laguna S 2.1
Not sourced
Muse Spark 1.2
Not sourced
Reasoning profile
Laguna S 2.1
Reasoning
Muse Spark 1.2
Reasoning
Weight access
Laguna S 2.1
Open Weight
Muse Spark 1.2
Proprietary
License
Laguna S 2.1
Open Weight
Muse Spark 1.2
Proprietary
Release date
Laguna S 2.1
2026-07-21
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
- Repository review: $0.0056 vs $0.07525. Cache-heavy agent loop: $0.006 vs $0.0975.
- 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 evidence8 rows
Agentic
Coding
Terminal-Bench 2.0
Laguna S 2.170.2%SourceMuse Spark 1.2—Not directly comparable
SWE Multilingual
Laguna S 2.178.5%SourceMuse Spark 1.2—Not directly comparable
SWE-bench Pro
Laguna S 2.159.4%SourceMuse Spark 1.2—Not directly comparable
deepSwe
Laguna S 2.140.4%SourceMuse Spark 1.259.3%SourceMuse Spark 1.2 leads this result
Terminal-Bench 2.1
Laguna S 2.1—Muse Spark 1.282.9%SourceNot directly comparable
Frequently asked questions
Which is better, Laguna S 2.1 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, Laguna S 2.1 or Muse Spark 1.2?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Laguna S 2.1 or Muse Spark 1.2?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Laguna S 2.1 or Muse Spark 1.2?
For the stated presets, chat costs $0.0002 on Laguna S 2.1 and $0.00337 on Muse Spark 1.2; repository review costs $0.0056 and $0.07525; the cache-heavy agent loop costs $0.006 and $0.0975. Costs use the listed standard API rates.
Which has the larger context window, Laguna S 2.1 or Muse Spark 1.2?
Both models list the same context window, 1M.
Related comparisons
Last updated August 5, 2026
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