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MiMo-V2.5-Pro vs Muse Spark 1.1

Updated October 7, 2026. Rank says Muse Spark 1.1 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 1.1 has the higher public score estimate, 65.95 versus 52.47, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 8 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Xiaomi logo

Xiaomi

52.47/100

Supported · Public rank #79

90% interval 36.3–68.6

Model B
Meta logo

Meta

65.95/100

Supported · Public rank #31

90% interval 58.0–73.9

Shared results
8
MiMo-V2.5-Pro only
5
Muse Spark 1.1 only
18
Like-for-like categories
3 / 8
Supported: MiMo-V2.5-Pro and Muse Spark 1.1How 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Muse Spark 1.1

    Muse Spark 1.1 has the higher public coding point estimate, 54.2 to 44.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    Muse Spark 1.1

    Muse Spark 1.1 has the higher public agentic point estimate, 56.9 to 36.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
Show secondary and unsupported calls
  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented
  • 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.

44.8MiMo-V2.5-Pro54.2Muse Spark 1.1

Like-for-like · BenchAlign v5.8

Muse Spark 1.1 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

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.

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.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 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

Like-for-like
MiMo-V2.5-Pro
36.9
Supported · #68/122
Muse Spark 1.1
56.9
Supported · #32/122
Basis
BenchAlign v5.8 lane · 5 vs 14 public rows
Reading
Muse Spark 1.1 leads · intervals overlap

Coding

Like-for-like
MiMo-V2.5-Pro
44.8
Supported · #53/146
Muse Spark 1.1
54.2
Supported · #35/146
Basis
BenchAlign v5.8 lane · 4 vs 4 public rows
Reading
Muse Spark 1.1 leads · intervals overlap

Knowledge

Like-for-like
MiMo-V2.5-Pro
50.7
Supported · #64/174
Muse Spark 1.1
66.7
Supported · #21/174
Basis
BenchAlign v5.8 lane · 4 vs 5 public rows
Reading
Muse Spark 1.1 leads · intervals overlap

Reasoning

Not comparable
MiMo-V2.5-Pro
77.1
Unranked · 2 rankable rows
Muse Spark 1.1
75.7
Unranked · 3 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
MiMo-V2.5-Pro
Not ranked
Muse Spark 1.1
78.3
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
MiMo-V2.5-Pro
Not ranked
Muse Spark 1.1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
MiMo-V2.5-Pro
92.4
#6/125
Muse Spark 1.1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
MiMo-V2.5-Pro
Not ranked
Muse Spark 1.1
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 v5.8) 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

MiMo-V2.5-Pro
API rate not published
Fits in one request
Muse Spark 1.1
API rate not published
Fits in one request

MiMo-V2.5-Pro has no comparable published API token rate. Muse Spark 1.1 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

MiMo-V2.5-Pro
API rate not published
Fits in one request
Muse Spark 1.1
API rate not published
Fits in one request

MiMo-V2.5-Pro has no comparable published API token rate. Muse Spark 1.1 has no comparable published API token rate.

Cache-heavy agent loop

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

MiMo-V2.5-Pro
API rate not published
Fits in one request
Cached-input rate unavailable
Muse Spark 1.1
API rate not published
Fits in one request
Cached-input rate unavailable

MiMo-V2.5-Pro has no comparable published API token rate. Muse Spark 1.1 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.

Context window

Maximum documented context; output-token limits may be lower.

MiMo-V2.5-Pro

1M

Muse Spark 1.1

1M

API model ID

MiMo-V2.5-Pro

Not sourced

Muse Spark 1.1

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

MiMo-V2.5-Pro

No comparable hosted API rate

Muse Spark 1.1

No comparable hosted API rate

Documented inputs

MiMo-V2.5-Pro

Not sourced

Muse Spark 1.1

Not sourced

Documented outputs

MiMo-V2.5-Pro

Not sourced

Muse Spark 1.1

Not sourced

Provider availability

MiMo-V2.5-Pro

Not sourced

Muse Spark 1.1

Not sourced

Reasoning profile

MiMo-V2.5-Pro

Reasoning

Muse Spark 1.1

Reasoning

Weight access

MiMo-V2.5-Pro

Proprietary

Muse Spark 1.1

Proprietary

License

MiMo-V2.5-Pro

Proprietary

Muse Spark 1.1

Proprietary

Release date

MiMo-V2.5-Pro

2026-04-22

Muse Spark 1.1

2026-07-09

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 1.1 has the higher public score estimate, 65.95 versus 52.47, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, MiMo-V2.5-Pro or Muse Spark 1.1?

Muse Spark 1.1 has the higher public score estimate, 65.95 versus 52.47, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, MiMo-V2.5-Pro or Muse Spark 1.1?

Muse Spark 1.1 has the higher public coding point estimate, 54.2 to 44.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, MiMo-V2.5-Pro or Muse Spark 1.1?

Muse Spark 1.1 has the higher public agentic tasks point estimate, 56.9 to 36.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, MiMo-V2.5-Pro or Muse Spark 1.1?

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, MiMo-V2.5-Pro or Muse Spark 1.1?

Both models list the same context window, 1M.

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

  • Claw-Eval

    MiMo-V2.5-Pro63.8%
    Source
    Muse Spark 1.1—

    Not directly comparable

  • τ³-bench results

    MiMo-V2.5-Pro72.9%
    Source
    Muse Spark 1.1—

    Not directly comparable

  • Terminal-Bench 2.0

    MiMo-V2.5-Pro68.4%
    Source
    Muse Spark 1.1—

    Not directly comparable

  • Gert Labs

    MiMo-V2.5-Pro62.70%
    Source
    Muse Spark 1.1—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    MiMo-V2.5-Pro57.3%
    Source
    Muse Spark 1.169.3%
    Source

    Muse Spark 1.1 leads this result

  • Terminal-Bench 2.1

    MiMo-V2.5-Pro—
    Muse Spark 1.180.0%
    Source

    Not directly comparable

  • MCP Atlas

    MiMo-V2.5-Pro—
    Muse Spark 1.188.1%
    Source

    Not directly comparable

  • Toolathlon

    MiMo-V2.5-Pro—
    Muse Spark 1.175.6%
    Source

    Not directly comparable

  • OSWorld-Verified

    MiMo-V2.5-Pro—
    Muse Spark 1.180.8%
    Source

    Not directly comparable

  • WebArena-Verified

    MiMo-V2.5-Pro—
    Muse Spark 1.169%
    Source

    Not directly comparable

  • DeepSearchQA

    MiMo-V2.5-Pro—
    Muse Spark 1.184.9%
    Source

    Not directly comparable

  • CyberGym

    MiMo-V2.5-Pro—
    Muse Spark 1.159.0%
    Source

    Not directly comparable

  • Finance Agent v2

    MiMo-V2.5-Pro—
    Muse Spark 1.157.2%
    Source

    Not directly comparable

  • deepSwe

    MiMo-V2.5-Pro—
    Muse Spark 1.153.3%
    Source

    Not directly comparable

  • OSWorld 2.0

    MiMo-V2.5-Pro—
    Muse Spark 1.114.2%
    Source

    Not directly comparable

  • JobBench

    MiMo-V2.5-Pro—
    Muse Spark 1.154.7%
    Source

    Not directly comparable

  • Cybench

    MiMo-V2.5-Pro—
    Muse Spark 1.192.9%
    Source

    Not directly comparable

  • ExploitGym

    MiMo-V2.5-Pro—
    Muse Spark 1.10.8%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    MiMo-V2.5-Pro57.2%
    Source
    Muse Spark 1.161.5%
    Source

    Muse Spark 1.1 leads this result

  • Terminal-Bench 2.0

    MiMo-V2.5-Pro68.4%
    Source
    Muse Spark 1.1—

    Not directly comparable

  • LiveCodeBench (Vals)

    MiMo-V2.5-Pro81.4%
    Source
    Muse Spark 1.185.9%
    Source

    Muse Spark 1.1 leads this result

  • SWE-bench (Vals)

    MiMo-V2.5-Pro74.0%
    Source
    Muse Spark 1.182.0%
    Source

    Muse Spark 1.1 leads this result

  • Terminal-Bench 2.1

    MiMo-V2.5-Pro—
    Muse Spark 1.180.0%
    Source

    Not directly comparable

Reasoning

  • MRCR 1M

    MiMo-V2.5-Pro—
    Muse Spark 1.154.1%
    Source

    Not directly comparable

Multimodal

  • CharXiv

    MiMo-V2.5-Pro—
    Muse Spark 1.188.4%
    Source

    Not directly comparable

  • BabyVision

    MiMo-V2.5-Pro—
    Muse Spark 1.176.3%
    Source

    Not directly comparable

Knowledge

  • HLE

    MiMo-V2.5-Pro48%
    Source
    Muse Spark 1.162.1%
    Source

    Muse Spark 1.1 leads this result

  • HLE w/o tools

    MiMo-V2.5-Pro34%
    Source
    Muse Spark 1.152.2%
    Source

    Muse Spark 1.1 leads this result

  • GPQA Diamond (Vals)

    MiMo-V2.5-Pro82.6%
    Source
    Muse Spark 1.191.2%
    Source

    Muse Spark 1.1 leads this result

  • MMLU-Pro (Vals)

    MiMo-V2.5-Pro84.6%
    Source
    Muse Spark 1.188.7%
    Source

    Muse Spark 1.1 leads this result

  • HealthBench Professional

    MiMo-V2.5-Pro—
    Muse Spark 1.159.3%
    Source

    Not directly comparable

31 public results · 8 shared

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Last updated October 7, 2026