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Data

Claude Opus 5.5 vs MiMo-V2.5

Updated November 6, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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Decision reading

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 resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Anthropic logo

Anthropic

86.32/100

Supported · Public rank #2

90% interval 81.4–91.2

Model B
Xiaomi logo

Xiaomi

—

Evidence status unavailable

90% interval unavailable

Shared results
1
Claude Opus 5.5 only
66
MiMo-V2.5 only
14
Like-for-like categories
1 / 8
Supported: Claude Opus 5.5How 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

    Claude Opus 5.5

    Claude Opus 5.5 has the higher public coding point estimate, 82.8 to 35.5, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
Show secondary and unsupported calls
  • Agentic work

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

    Not enough matched evidence

    MiMo-V2.5 is scored on Estimated evidence for agentic, 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

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.

82.8Claude Opus 5.535.5MiMo-V2.5

Like-for-like · BenchAlign v5.8

Claude Opus 5.5 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.

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.

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.

Coding

Like-for-like
Claude Opus 5.5
82.8
Supported · #1/157
MiMo-V2.5
35.5
Supported · #84/157
Basis
BenchAlign v5.8 lane · 13 vs 4 public rows
Reading
Claude Opus 5.5 leads

Agentic

Directional only
Claude Opus 5.5
89.3
Supported · #1/131
MiMo-V2.5
37.0
Estimated · #77/131
Basis
BenchAlign v5.8 lane · 17 vs 6 public rows
Reading
Directional only

Multimodal

Directional only
Claude Opus 5.5
91.6
#3/59
MiMo-V2.5
70.9
#36/59
Basis
Provisional lane · 1 vs 2 weighted rows
Reading
Directional only

Reasoning

Not comparable
Claude Opus 5.5
84.4
#4/25
MiMo-V2.5
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 5.5
89.4
Supported · #1/178
MiMo-V2.5
Not ranked
Basis
BenchAlign v5.8 lane · 16 vs 2 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 5.5
Not ranked
MiMo-V2.5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 5.5
Not ranked
MiMo-V2.5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Opus 5.5
93.8
Unranked · 4 rankable rows
MiMo-V2.5
Not ranked
Basis
Provisional lane · 2 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

Claude Opus 5.5
$0.014
Fits in one request
MiMo-V2.5
API rate not published
Fits in one request

MiMo-V2.5 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 5.5
$0.26
Fits in one request
MiMo-V2.5
API rate not published
Fits in one request

MiMo-V2.5 has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Opus 5.5
$0.32
Fits in one request
MiMo-V2.5
API rate not published
Fits in one request
Cached-input rate unavailable

MiMo-V2.5 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.

Cached-input rate

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

Claude Opus 5.5

$0.2 per 1M cached input tokens

Claude Opus 5.5 model documentation

MiMo-V2.5

No comparable hosted API rate

Reasoning profile

Claude Opus 5.5

Reasoning

MiMo-V2.5

Reasoning

Weight access

Claude Opus 5.5

Proprietary

MiMo-V2.5

Proprietary

License

Claude Opus 5.5

Proprietary

MiMo-V2.5

Proprietary

Release date

Claude Opus 5.5

2026-09-22

MiMo-V2.5

2026-04-22

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
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, Claude Opus 5.5 or MiMo-V2.5?

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, Claude Opus 5.5 or MiMo-V2.5?

Claude Opus 5.5 has the higher public coding point estimate, 82.8 to 35.5, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Claude Opus 5.5 or MiMo-V2.5?

Claude Opus 5.5 scores higher for agentic tasks on the public lane, 89.3 to 37. MiMo-V2.5 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, Claude Opus 5.5 or MiMo-V2.5?

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, Claude Opus 5.5 or MiMo-V2.5?

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 evidence81 rows

Agentic

  • Terminal-Bench 4.0

    Claude Opus 5.566.40%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Opus 5.558.7%
    Source
    MiMo-V2.5—

    Not directly comparable

  • AutomationBench

    Claude Opus 5.540.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • HLE w/ tools

    Claude Opus 5.567.7%
    Source
    MiMo-V2.5—

    Not directly comparable

  • OSWorld 2.0

    Claude Opus 5.548.7%
    Source
    MiMo-V2.5—

    Not directly comparable

  • LAB all-pass (Harvey held-out)

    Claude Opus 5.58.3%
    Source
    MiMo-V2.5—

    Not directly comparable

  • LAB criterion-pass (Harvey held-out)

    Claude Opus 5.591.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Toolathlon-Verified

    Claude Opus 5.577.8%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude Opus 5.582.4%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Opus 5.572.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Opus 5.526.9 turns
    Source
    MiMo-V2.5—

    Not directly comparable

  • CWE-bench v1

    Claude Opus 5.567.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Hermes Index

    Claude Opus 5.563.3%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Hermes Bench

    Claude Opus 5.576.7%
    Source
    MiMo-V2.5—

    Not directly comparable

  • MazeBench

    Claude Opus 5.513%
    Source
    MiMo-V2.5—

    Not directly comparable

  • OSWorld 2.1

    Claude Opus 5.581.8%
    Source
    MiMo-V2.5—

    Not directly comparable

  • OSWorld 2.1 Offline

    Claude Opus 5.587.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Claw-Eval

    Claude Opus 5.5—
    MiMo-V2.562.3%
    Source

    Not directly comparable

  • MM-ClawBench

    Claude Opus 5.5—
    MiMo-V2.523.8%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 5.5—
    MiMo-V2.565.8%
    Source

    Not directly comparable

  • Gert Labs

    Claude Opus 5.5—
    MiMo-V2.546.89%
    Source

    Not directly comparable

  • ResearchClawBench

    Claude Opus 5.5—
    MiMo-V2.516.9%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Opus 5.5—
    MiMo-V2.560.7%
    Source

    Not directly comparable

Coding

  • ScarfBench

    Claude Opus 5.570.5%
    Source
    MiMo-V2.5—

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Opus 5.554.4%
    Source
    MiMo-V2.5—

    Not directly comparable

  • CursorBench 4.0

    Claude Opus 5.557.8%
    Source
    MiMo-V2.5—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 5.589.9%
    Source
    MiMo-V2.556.1%
    Source

    Claude Opus 5.5 leads this result

  • SWE Multilingual

    Claude Opus 5.593.9%
    Source
    MiMo-V2.5—

    Not directly comparable

  • SWE Multimodal

    Claude Opus 5.561.4%
    Source
    MiMo-V2.5—

    Not directly comparable

  • DeepSWE

    Claude Opus 5.574.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • FrontierCode 1.1 Extended

    Claude Opus 5.563.6%
    Source
    MiMo-V2.5—

    Not directly comparable

  • FrontierSWE v2

    Claude Opus 5.562.3%
    Source
    MiMo-V2.5—

    Not directly comparable

  • ProgramBench

    Claude Opus 5.591.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • PostTrainBench v1.1

    Claude Opus 5.549.3%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Bug Hunt Bench

    Claude Opus 5.541.7 fixes
    Source
    MiMo-V2.5—

    Not directly comparable

  • FrontierCode 2.0

    Claude Opus 5.545.5%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 5.5—
    MiMo-V2.565.8%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Opus 5.5—
    MiMo-V2.581.5%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    Claude Opus 5.5—
    MiMo-V2.571.0%
    Source

    Not directly comparable

Reasoning

  • STEMBench

    Claude Opus 5.52.62
    Source
    MiMo-V2.5—

    Not directly comparable

  • ARC-AGI-1

    Claude Opus 5.597.50%
    Source
    MiMo-V2.5—

    Not directly comparable

  • ARC-AGI-2

    Claude Opus 5.591.7%
    Source
    MiMo-V2.5—

    Not directly comparable

  • GraphWalks BFS 256K–1M

    Claude Opus 5.566.8%
    Source
    MiMo-V2.5—

    Not directly comparable

Multimodal

  • ExtractBench Pro

    Claude Opus 5.551%
    Source
    MiMo-V2.5—

    Not directly comparable

  • ExtractBench (LlamaIndex)

    Claude Opus 5.586.06%
    Source
    MiMo-V2.5—

    Not directly comparable

  • ParseBench

    Claude Opus 5.578.80%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Chartography (tools)

    Claude Opus 5.589.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Chartography (no tools)

    Claude Opus 5.564.4%
    Source
    MiMo-V2.5—

    Not directly comparable

  • BenchCAD Vision2Code (no tools)

    Claude Opus 5.50.730
    Source
    MiMo-V2.5—

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    Claude Opus 5.50.962
    Source
    MiMo-V2.5—

    Not directly comparable

  • Biomedical image analysis

    Claude Opus 5.571.4%
    Source
    MiMo-V2.5—

    Not directly comparable

  • OfficeQA

    Claude Opus 5.578.9%
    Source
    MiMo-V2.5—

    Not directly comparable

  • OfficeQA Pro

    Claude Opus 5.567.7%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Video-MME (with subtitle)

    Claude Opus 5.5—
    MiMo-V2.587.7%
    Source

    Not directly comparable

  • CharXiv

    Claude Opus 5.5—
    MiMo-V2.581%
    Source

    Not directly comparable

  • MMMU-Pro

    Claude Opus 5.5—
    MiMo-V2.577.9%
    Source

    Not directly comparable

Knowledge

  • HLE w/o tools

    Claude Opus 5.564.4%
    Source
    MiMo-V2.5—

    Not directly comparable

  • HealthBench (raw)

    Claude Opus 5.568.1%
    Source
    MiMo-V2.5—

    Not directly comparable

  • HealthBench (length-adjusted)

    Claude Opus 5.560.6%
    Source
    MiMo-V2.5—

    Not directly comparable

  • HealthBench Professional

    Claude Opus 5.565.6%
    Source
    MiMo-V2.5—

    Not directly comparable

  • HealthBench Professional (raw)

    Claude Opus 5.577.1%
    Source
    MiMo-V2.5—

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Claude Opus 5.589.3%
    Source
    MiMo-V2.5—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Claude Opus 5.550.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • SpatialBench Verified

    Claude Opus 5.572.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • SingleCellBench

    Claude Opus 5.561.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Morphology-to-molecule matching

    Claude Opus 5.534.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Medicinal chemistry

    Claude Opus 5.563.5%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Protein Design

    Claude Opus 5.560.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Protein Design library ranking

    Claude Opus 5.556.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • De novo protein-binder design

    Claude Opus 5.582.6%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Protocols (troubleshooting)

    Claude Opus 5.573.7%
    Source
    MiMo-V2.5—

    Not directly comparable

  • Protocols (understanding)

    Claude Opus 5.569.0%
    Source
    MiMo-V2.5—

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Opus 5.5—
    MiMo-V2.581.6%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Opus 5.5—
    MiMo-V2.582.9%
    Source

    Not directly comparable

Multilingual

  • GMMLU

    Claude Opus 5.594.3%
    Source
    MiMo-V2.5—

    Not directly comparable

  • MILU

    Claude Opus 5.593.1%
    Source
    MiMo-V2.5—

    Not directly comparable

Instruction following

  • Gray Swan IPI (15 attempts)

    Claude Opus 5.51.0%
    Source
    MiMo-V2.5—

    Not directly comparable

Math

  • ArXivMath Aug. 2026 (no tools)

    Claude Opus 5.591.2%
    Source
    MiMo-V2.5—

    Not directly comparable

  • ArXivMath Aug. 2026 (tools)

    Claude Opus 5.596.9%
    Source
    MiMo-V2.5—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 5.591.228%
    Source
    MiMo-V2.5—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 5.595.000%
    Source
    MiMo-V2.5—

    Not directly comparable

81 public results · 1 shared

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Last updated November 6, 2026