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BenchLM

dots3-note Preview vs Muse Spark 1.2

Updated September 28, 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.

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Decision reading

Muse Spark 1.2 has the higher public score estimate, 64.92 versus 62.64, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Dots Studio

62.64/100

Estimated · Public rank #39

90% interval 52.8–72.5

Model B
Meta logo

Meta

64.92/100

Estimated · Public rank #31

90% interval 59.2–70.7

Shared results
2
dots3-note Preview only
29
Muse Spark 1.2 only
6
Like-for-like categories
0 / 8
Estimated: dots3-note Preview and Muse Spark 1.2How the comparison works

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

    Dots3-note Preview 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

    Dots3-note Preview is scored on Estimated evidence for agentic, so the reading is 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

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.

—dots3-note Preview55.2Muse Spark 1.2

Not comparable · BenchAlign v5.7

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 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.

Agentic

Directional only
dots3-note Preview
56.4
Estimated · #28/117
Muse Spark 1.2
59.3
Supported · #22/117
Basis
BenchAlign v5.7 lane · 9 vs 2 public rows
Reading
Directional only

Coding

Not comparable
dots3-note Preview
Not ranked
Muse Spark 1.2
55.2
Supported · #29/142
Basis
BenchAlign v5.7 lane · 7 vs 5 public rows
Reading
Not comparable

Reasoning

Not comparable
dots3-note Preview
72.9
Unranked · 1 rankable row
Muse Spark 1.2
76.6
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
dots3-note Preview
67.2
Unranked · 10 rankable rows
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
dots3-note Preview
Not ranked
Muse Spark 1.2
64.9
Supported · #24/168
Basis
BenchAlign v5.7 lane · 1 vs 1 public rows
Reading
Not comparable

Multilingual

Not comparable
dots3-note Preview
Not ranked
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
dots3-note Preview
85.2
#37/124
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
dots3-note Preview
Not ranked
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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

dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Muse Spark 1.2
$0.00338
Fits in one request

dots3-note Preview has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Muse Spark 1.2
$0.07525
Fits in one request

dots3-note Preview has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Muse Spark 1.2
$0.0975
Fits in one request

dots3-note Preview has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Documented inputs

dots3-note Preview

Not sourced

Muse Spark 1.2

Not sourced

Documented outputs

dots3-note Preview

Not sourced

Muse Spark 1.2

Not sourced

Provider availability

dots3-note Preview

Not sourced

Muse Spark 1.2

Not sourced

Reasoning profile

dots3-note Preview

Reasoning

Muse Spark 1.2

Reasoning

Weight access

dots3-note Preview

Open Weight

Muse Spark 1.2

Proprietary

License

dots3-note Preview

Open Weight

Muse Spark 1.2

Proprietary

Release date

dots3-note Preview

2026-08-14

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, 64.92 versus 62.64, but the 90% score intervals overlap.
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.

Questions

Which is better, dots3-note Preview or Muse Spark 1.2?

Muse Spark 1.2 has the higher public score estimate, 64.92 versus 62.64, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, dots3-note Preview or Muse Spark 1.2?

Dots3-note Preview is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, dots3-note Preview or Muse Spark 1.2?

Muse Spark 1.2 scores higher for agentic tasks on the public lane, 59.3 to 56.4. Dots3-note Preview is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, dots3-note Preview 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, dots3-note Preview or Muse Spark 1.2?

Muse Spark 1.2 has the larger documented context window: 1M, compared with 512K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence37 rows

Agentic

  • Claw-Eval

    dots3-note Preview73.4%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.1

    dots3-note Preview75.1%
    Source
    Muse Spark 1.282.9%
    Source

    Muse Spark 1.2 leads this result

  • Toolathlon-Verified

    dots3-note Preview55.6%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • skillsBench

    dots3-note Preview52.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • APEX-Agents

    dots3-note Preview30.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • BrowseComp

    dots3-note Preview83.3%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • HLE w/ tools

    dots3-note Preview52.6%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • DeepSearchQA

    dots3-note Preview92.1%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • WideResearch

    dots3-note Preview78.9%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    dots3-note Preview—
    Muse Spark 1.269.7%
    Source

    Not directly comparable

Coding

  • Codeforces

    dots3-note Preview3056.0
    Source
    Muse Spark 1.2—

    Not directly comparable

  • LiveCodeBench v6

    dots3-note Preview91.5%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.1

    dots3-note Preview75.1%
    Source
    Muse Spark 1.282.9%
    Source

    Muse Spark 1.2 leads this result

  • SWE-bench Verified

    dots3-note Preview78.4%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SWE Multilingual

    dots3-note Preview75.7%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SWE-bench Pro

    dots3-note Preview61%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • NL2Repo

    dots3-note Preview49.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • DeepSWE

    dots3-note Preview—
    Muse Spark 1.259.3%
    Source

    Not directly comparable

  • VulcanBench v3

    dots3-note Preview—
    Muse Spark 1.287.0%
    Source

    Not directly comparable

  • FrontierSWE v2

    dots3-note Preview—
    Muse Spark 1.212.0%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    dots3-note Preview—
    Muse Spark 1.286.6%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    dots3-note Preview81.4%
    Source
    Muse Spark 1.2—

    Not directly comparable

Multimodal

  • SimpleVQA

    dots3-note Preview72.5%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MMMU-Pro

    dots3-note Preview79.1%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MathVision

    dots3-note Preview87.7%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • ZeroBench

    dots3-note Preview19.0%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • CharXiv w/o tools

    dots3-note Preview83.1%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • GDP.pdf (no tools)

    dots3-note Preview60.7%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • PerceptionBench

    dots3-note Preview53.4%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • BabyVision

    dots3-note Preview50.0%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MMVU

    dots3-note Preview79.9%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • VideoMMMU

    dots3-note Preview86.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

Knowledge

  • HLE

    dots3-note Preview52.6%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MMLU-Pro (Vals)

    dots3-note Preview—
    Muse Spark 1.288.3%
    Source

    Not directly comparable

Instruction following

  • IFBench

    dots3-note Preview80.4%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • IFEval

    dots3-note Preview93.9%
    Source
    Muse Spark 1.2—

    Not directly comparable

Math

  • IMOAnswerBench

    dots3-note Preview90.9%
    Source
    Muse Spark 1.2—

    Not directly comparable

37 public results · 2 shared

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Last updated September 28, 2026