Agentic
Like-for-like- MiMo-V2.5-Pro
- 40.8
- Supported · #118/151
- Qwen3.7 Plus
- 37.7
- Supported · #126/151
- Basis
- BenchAlign lane · 5 vs 11 public rows
- Reading
- MiMo-V2.5-Pro leads · intervals overlap
MiMo-V2.5-Pro vs Qwen3.7 Plus
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
MiMo-V2.5-Pro has the higher public score estimate, 65.41 versus 62.29, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Agentic work
Tool use, computer use, and multi-step task completion
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads on the public agentic lane, 40.8 to 37.7, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
MiMo-V2.5-Pro and Qwen3.7 Plus are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
7 MiMo-V2.5-Pro only
6 Shared
46 Qwen3.7 Plus only
- Shared results
- 6
- MiMo-V2.5-Pro only
- 7
- Qwen3.7 Plus only
- 46
- Like-for-like categories
- 1 / 8
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign 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-V2.5-Pro
- 57.1
- Estimated · #36/183
- Qwen3.7 Plus
- 53.1
- Estimated · #51/183
- Basis
- BenchAlign lane · 4 vs 7 public rows
- Reading
- Directional only
Knowledge
Directional only- MiMo-V2.5-Pro
- 55.5
- Supported · #58/181
- Qwen3.7 Plus
- 56.8
- Estimated · #50/181
- Basis
- BenchAlign lane · 4 vs 7 public rows
- Reading
- Directional only
Instruction following
Directional only- MiMo-V2.5-Pro
- 93.5
- #6/120
- Qwen3.7 Plus
- 91.1
- #17/120
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- MiMo-V2.5-Pro
- 76.9
- Unranked · 2 rankable rows
- Qwen3.7 Plus
- 73.7
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- MiMo-V2.5-Pro
- Not ranked
- Qwen3.7 Plus
- 78.3
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- MiMo-V2.5-Pro
- Not ranked
- Qwen3.7 Plus
- 78.9
- #3/12
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- MiMo-V2.5-Pro
- Not ranked
- Qwen3.7 Plus
- 72.5
- #18/48
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
| Category | MiMo-V2.5-Pro | Qwen3.7 Plus | Basis | Reading |
|---|---|---|---|---|
| Agentic | 40.8Supported · #118/151 | 37.7Supported · #126/151 | Like-for-likeBenchAlign lane · 5 vs 11 public rows | MiMo-V2.5-Pro leads · intervals overlap |
| Coding | 57.1Estimated · #36/183 | 53.1Estimated · #51/183 | Directional onlyBenchAlign lane · 4 vs 7 public rows | Directional only |
| Knowledge | 55.5Supported · #58/181 | 56.8Estimated · #50/181 | Directional onlyBenchAlign lane · 4 vs 7 public rows | Directional only |
| Instruction following | 93.5#6/120 | 91.1#17/120 | Directional onlyProvisional lane · 0 vs 1 weighted rows | Directional only |
| Reasoning | 76.9Unranked · 2 rankable rows | 73.7Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | Not ranked | 78.3Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | 78.9#3/12 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | 72.5#18/48 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
HLE
Knowledge
Terminal-Bench 2.0
Agentic
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
- MiMo-V2.5-Pro
- API rate not published
- Fits in one request
- Qwen3.7 Plus
- API rate not published
- Fits in one request
MiMo-V2.5-Pro has no comparable published API token rate. Qwen3.7 Plus 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
- Qwen3.7 Plus
- API rate not published
- Fits in one request
MiMo-V2.5-Pro has no comparable published API token rate. Qwen3.7 Plus 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
- Qwen3.7 Plus
- API rate not published
- Fits in one request
- Cached-input rate unavailable
MiMo-V2.5-Pro has no comparable published API token rate. Qwen3.7 Plus 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.
SpecificationMiMo-V2.5-ProQwen3.7 Plus
Context window
Maximum documented context; output-token limits may be lower.
MiMo-V2.5-Pro
1M
Qwen3.7 Plus
1M
API model ID
MiMo-V2.5-Pro
Not sourced
Qwen3.7 Plus
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
Qwen3.7 Plus
No comparable hosted API rate
Documented inputs
MiMo-V2.5-Pro
Not sourced
Qwen3.7 Plus
Not sourced
Documented outputs
MiMo-V2.5-Pro
Not sourced
Qwen3.7 Plus
Not sourced
Provider availability
MiMo-V2.5-Pro
Not sourced
Qwen3.7 Plus
Not sourced
Reasoning profile
MiMo-V2.5-Pro
Reasoning
Qwen3.7 Plus
Reasoning
Weight access
MiMo-V2.5-Pro
Proprietary
Qwen3.7 Plus
Proprietary
License
MiMo-V2.5-Pro
Proprietary
Qwen3.7 Plus
Proprietary
Release date
MiMo-V2.5-Pro
2026-04-22
Qwen3.7 Plus
2026-06-03
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
- MiMo-V2.5-Pro has the higher public score estimate, 65.41 versus 62.29, 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.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence59 rows
Agentic
Claw-Eval
MiMo-V2.5-Pro63.8%SourceQwen3.7 Plus62.7%SourceMiMo-V2.5-Pro leads this result
τ³-bench results
MiMo-V2.5-Pro72.9%SourceQwen3.7 Plus—Not directly comparable
Terminal-Bench 2.0
MiMo-V2.5-Pro68.4%SourceQwen3.7 Plus70.3%SourceQwen3.7 Plus leads this result
Gert Labs
MiMo-V2.5-Pro62.70%SourceQwen3.7 Plus—Not directly comparable
Terminal-Bench 2.1 (Vals)
MiMo-V2.5-Pro57.3%SourceQwen3.7 Plus52.8%SourceMiMo-V2.5-Pro leads this result
QwenClawBench
MiMo-V2.5-Pro—Qwen3.7 Plus61.8%SourceNot directly comparable
BFCL v4
MiMo-V2.5-Pro—Qwen3.7 Plus72.9%SourceNot directly comparable
MCP Atlas
MiMo-V2.5-Pro—Qwen3.7 Plus73.2%SourceNot directly comparable
VITA-Bench
MiMo-V2.5-Pro—Qwen3.7 Plus45.6%SourceNot directly comparable
DeepPlanning
MiMo-V2.5-Pro—Qwen3.7 Plus62.3%SourceNot directly comparable
OSWorld-Verified
MiMo-V2.5-Pro—Qwen3.7 Plus73.3%SourceNot directly comparable
AndroidWorld
MiMo-V2.5-Pro—Qwen3.7 Plus81.0%SourceNot directly comparable
OSWorld 2.0
MiMo-V2.5-Pro—Qwen3.7 Plus2.8%SourceNot directly comparable
Coding
SWE-bench Pro
MiMo-V2.5-Pro57.2%SourceQwen3.7 Plus57.6%SourceQwen3.7 Plus leads this result
Terminal-Bench 2.0
MiMo-V2.5-Pro68.4%SourceQwen3.7 Plus70.3%SourceQwen3.7 Plus leads this result
LiveCodeBench (Vals)
MiMo-V2.5-Pro81.4%SourceQwen3.7 Plus—Not directly comparable
SWE-bench (Vals)
MiMo-V2.5-Pro74.0%SourceQwen3.7 Plus—Not directly comparable
SWE-bench Verified
MiMo-V2.5-Pro—Qwen3.7 Plus77.7%SourceNot directly comparable
SWE Multilingual
MiMo-V2.5-Pro—Qwen3.7 Plus75.8%SourceNot directly comparable
NL2Repo
MiMo-V2.5-Pro—Qwen3.7 Plus41.1%SourceNot directly comparable
SciCode
MiMo-V2.5-Pro—Qwen3.7 Plus51.3%SourceNot directly comparable
LiveCodeBench
MiMo-V2.5-Pro—Qwen3.7 Plus89.6%SourceNot directly comparable
Reasoning
Knowledge
HLE
MiMo-V2.5-Pro48%SourceQwen3.7 Plus34.7%SourceMiMo-V2.5-Pro leads this result
HLE w/o tools
MiMo-V2.5-Pro34%SourceQwen3.7 Plus—Not directly comparable
GPQA Diamond (Vals)
MiMo-V2.5-Pro82.6%SourceQwen3.7 Plus—Not directly comparable
MMLU-Pro (Vals)
MiMo-V2.5-Pro84.6%SourceQwen3.7 Plus—Not directly comparable
GPQA
MiMo-V2.5-Pro—Qwen3.7 Plus90.3%SourceNot directly comparable
GPQA-D
MiMo-V2.5-Pro—Qwen3.7 Plus90.3%SourceNot directly comparable
MMLU-Pro
MiMo-V2.5-Pro—Qwen3.7 Plus88.5%SourceNot directly comparable
MMLU-Redux
MiMo-V2.5-Pro—Qwen3.7 Plus94.5%SourceNot directly comparable
SuperGPQA
MiMo-V2.5-Pro—Qwen3.7 Plus71.4%SourceNot directly comparable
MMMLU
MiMo-V2.5-Pro—Qwen3.7 Plus89.0%SourceNot directly comparable
Math
Multilingual
MMLU-ProX
MiMo-V2.5-Pro—Qwen3.7 Plus85.4%SourceNot directly comparable
NOVA-63
MiMo-V2.5-Pro—Qwen3.7 Plus58.8%SourceNot directly comparable
INCLUDE
MiMo-V2.5-Pro—Qwen3.7 Plus83.0%SourceNot directly comparable
MAXIFE
MiMo-V2.5-Pro—Qwen3.7 Plus88.8%SourceNot directly comparable
PolyMath
MiMo-V2.5-Pro—Qwen3.7 Plus84.0%SourceNot directly comparable
Multimodal
MMMU-Pro
MiMo-V2.5-Pro—Qwen3.7 Plus79%SourceNot directly comparable
MathVision
MiMo-V2.5-Pro—Qwen3.7 Plus90.3%SourceNot directly comparable
CharXiv
MiMo-V2.5-Pro—Qwen3.7 Plus85.9%SourceNot directly comparable
ERQA
MiMo-V2.5-Pro—Qwen3.7 Plus69.8%SourceNot directly comparable
MedXpertQA (MM)
MiMo-V2.5-Pro—Qwen3.7 Plus71.0%SourceNot directly comparable
ScreenSpot Pro
MiMo-V2.5-Pro—Qwen3.7 Plus79.0%SourceNot directly comparable
SimpleVQA
MiMo-V2.5-Pro—Qwen3.7 Plus81.7%SourceNot directly comparable
MMSearch-Plus
MiMo-V2.5-Pro—Qwen3.7 Plus41.4%SourceNot directly comparable
RealWorldQA
MiMo-V2.5-Pro—Qwen3.7 Plus86.9%SourceNot directly comparable
OmniDocBench 1.5
MiMo-V2.5-Pro—Qwen3.7 Plus91.4%SourceNot directly comparable
OCRBench V2
MiMo-V2.5-Pro—Qwen3.7 Plus70.7%SourceNot directly comparable
ODINW13
MiMo-V2.5-Pro—Qwen3.7 Plus51.1%SourceNot directly comparable
Video-MME (with subtitle)
MiMo-V2.5-Pro—Qwen3.7 Plus88.0%SourceNot directly comparable
VideoMMMU
MiMo-V2.5-Pro—Qwen3.7 Plus85.4%SourceNot directly comparable
MLVU (M-Avg)
MiMo-V2.5-Pro—Qwen3.7 Plus87.4%SourceNot directly comparable
Instruction following
Frequently asked questions
Which is better, MiMo-V2.5-Pro or Qwen3.7 Plus?
MiMo-V2.5-Pro has the higher public score estimate, 65.41 versus 62.29, 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 Qwen3.7 Plus?
MiMo-V2.5-Pro scores higher for coding on the public lane, 57.1 to 53.1. MiMo-V2.5-Pro and Qwen3.7 Plus are 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-V2.5-Pro or Qwen3.7 Plus?
MiMo-V2.5-Pro leads the public agentic tasks lane, 40.8 to 37.7, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, MiMo-V2.5-Pro or Qwen3.7 Plus?
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 Qwen3.7 Plus?
Both models list the same context window, 1M.
Related comparisons
Last updated September 4, 2026
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