Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
MiMo-V2-Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
MiMo-V2-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.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 0
- MiMo-V2-Pro only
- 4
- Muse Spark 1.1 only
- 26
- Like-for-like categories
- 0 / 8
Estimated: MiMo-V2-Pro · Supported: Muse Spark 1.1. Conditional ranges do not establish rank confidence.How 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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
MiMo-V2-Pro is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documentedChat 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-ratesCache-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-ratesRepository 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.
40.8MiMo-V2-Pro54.2Muse Spark 1.1
Directional only · 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.
4 MiMo-V2-Pro only
26 Muse Spark 1.1 only
2 categories rest 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 v5.8 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.
Coding
Directional only- MiMo-V2-Pro
- 40.8
- Estimated · #64/146
- Muse Spark 1.1
- 54.2
- Supported · #35/146
- Basis
- BenchAlign v5.8 lane · 1 vs 4 public rows
- Reading
- Directional only
Knowledge
Directional only- MiMo-V2-Pro
- 48.7
- Estimated · #73/174
- Muse Spark 1.1
- 66.7
- Supported · #21/174
- Basis
- BenchAlign v5.8 lane · 0 vs 5 public rows
- Reading
- Directional only
Agentic
Not comparable- MiMo-V2-Pro
- Not ranked
- Muse Spark 1.1
- 56.9
- Supported · #32/122
- Basis
- BenchAlign v5.8 lane · 3 vs 14 public rows
- Reading
- Not comparable
Reasoning
Not comparable- MiMo-V2-Pro
- 69.2
- 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-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-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-Pro
- 82.6
- #46/125
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- MiMo-V2-Pro
- Not ranked
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | MiMo-V2-Pro | Muse Spark 1.1 | Basis | Reading |
|---|---|---|---|---|
| Coding | 40.8Estimated · #64/146 | 54.2Supported · #35/146 | Directional onlyBenchAlign v5.8 lane · 1 vs 4 public rows | Directional only |
| Knowledge | 48.7Estimated · #73/174 | 66.7Supported · #21/174 | Directional onlyBenchAlign v5.8 lane · 0 vs 5 public rows | Directional only |
| Agentic | Not ranked | 56.9Supported · #32/122 | Not comparableBenchAlign v5.8 lane · 3 vs 14 public rows | Not comparable |
| Reasoning | 69.2Unranked · 2 rankable rows | 75.7Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 78.3Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 82.6#46/125 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 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 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-Pro
- API rate not published
- Fits in one request
- Muse Spark 1.1
- API rate not published
- Fits in one request
MiMo-V2-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-Pro
- API rate not published
- Fits in one request
- Muse Spark 1.1
- API rate not published
- Fits in one request
MiMo-V2-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-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-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.
SpecificationMiMo-V2-ProMuse Spark 1.1
Context window
Maximum documented context; output-token limits may be lower.
MiMo-V2-Pro
1M
Muse Spark 1.1
1M
API model ID
MiMo-V2-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-Pro
No comparable hosted API rate
Muse Spark 1.1
No comparable hosted API rate
Documented inputs
MiMo-V2-Pro
Not sourced
Muse Spark 1.1
Not sourced
Documented outputs
MiMo-V2-Pro
Not sourced
Muse Spark 1.1
Not sourced
Provider availability
MiMo-V2-Pro
Not sourced
Muse Spark 1.1
Not sourced
Reasoning profile
MiMo-V2-Pro
Reasoning
Muse Spark 1.1
Reasoning
Weight access
MiMo-V2-Pro
Proprietary
Muse Spark 1.1
Proprietary
License
MiMo-V2-Pro
Proprietary
Muse Spark 1.1
Proprietary
Release date
MiMo-V2-Pro
2026-03-18
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
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- 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-Pro or Muse Spark 1.1?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, MiMo-V2-Pro or Muse Spark 1.1?
Muse Spark 1.1 scores higher for coding on the public lane, 54.2 to 40.8. MiMo-V2-Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, MiMo-V2-Pro or Muse Spark 1.1?
MiMo-V2-Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, MiMo-V2-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-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 evidence30 rows
Agentic
Claw-Eval
MiMo-V2-Pro57.8%SourceMuse Spark 1.1—Not directly comparable
Gert Labs
MiMo-V2-Pro36.68%SourceMuse Spark 1.1—Not directly comparable
ResearchClawBench
MiMo-V2-Pro15.3%SourceMuse Spark 1.1—Not directly comparable
Terminal-Bench 2.1
MiMo-V2-Pro—Muse Spark 1.180.0%SourceNot directly comparable
MCP Atlas
MiMo-V2-Pro—Muse Spark 1.188.1%SourceNot directly comparable
Toolathlon
MiMo-V2-Pro—Muse Spark 1.175.6%SourceNot directly comparable
OSWorld-Verified
MiMo-V2-Pro—Muse Spark 1.180.8%SourceNot directly comparable
WebArena-Verified
MiMo-V2-Pro—Muse Spark 1.169%SourceNot directly comparable
DeepSearchQA
MiMo-V2-Pro—Muse Spark 1.184.9%SourceNot directly comparable
CyberGym
MiMo-V2-Pro—Muse Spark 1.159.0%SourceNot directly comparable
Finance Agent v2
MiMo-V2-Pro—Muse Spark 1.157.2%SourceNot directly comparable
deepSwe
MiMo-V2-Pro—Muse Spark 1.153.3%SourceNot directly comparable
OSWorld 2.0
MiMo-V2-Pro—Muse Spark 1.114.2%SourceNot directly comparable
JobBench
MiMo-V2-Pro—Muse Spark 1.154.7%SourceNot directly comparable
Cybench
MiMo-V2-Pro—Muse Spark 1.192.9%SourceNot directly comparable
ExploitGym
MiMo-V2-Pro—Muse Spark 1.10.8%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
MiMo-V2-Pro—Muse Spark 1.169.3%SourceNot directly comparable
Coding
SWE-bench Verified
MiMo-V2-Pro78%SourceMuse Spark 1.1—Not directly comparable
Terminal-Bench 2.1
MiMo-V2-Pro—Muse Spark 1.180.0%SourceNot directly comparable
SWE-bench Pro
MiMo-V2-Pro—Muse Spark 1.161.5%SourceNot directly comparable
LiveCodeBench (Vals)
MiMo-V2-Pro—Muse Spark 1.185.9%SourceNot directly comparable
SWE-bench (Vals)
MiMo-V2-Pro—Muse Spark 1.182.0%SourceNot directly comparable
Reasoning
MRCR 1M
MiMo-V2-Pro—Muse Spark 1.154.1%SourceNot directly comparable
Multimodal
Knowledge
HLE
MiMo-V2-Pro—Muse Spark 1.162.1%SourceNot directly comparable
HLE w/o tools
MiMo-V2-Pro—Muse Spark 1.152.2%SourceNot directly comparable
HealthBench Professional
MiMo-V2-Pro—Muse Spark 1.159.3%SourceNot directly comparable
GPQA Diamond (Vals)
MiMo-V2-Pro—Muse Spark 1.191.2%SourceNot directly comparable
MMLU-Pro (Vals)
MiMo-V2-Pro—Muse Spark 1.188.7%SourceNot directly comparable
30 public results · 0 shared
Watch MiMo-V2-Pro vs Muse Spark 1.1
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 5,500+ readers.
Last updated October 7, 2026