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BenchLM
Anthropic logo
Model A
Claude Haiku 4.5

Anthropic

52.91/100

Supported · Public rank #110

90% interval 40.5–65.4

Claude Haiku 4.5 vs MiMo-V2-Pro

Updated September 15, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Xiaomi logo
Model B
MiMo-V2-Pro

Xiaomi

62.79/100

Supported · Public rank #50

90% interval 51.9–73.7

Decision reading

MiMo-V2-Pro has the higher public score estimate, 62.79 versus 52.91, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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

    MiMo-V2-Pro

    MiMo-V2-Pro 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

    MiMo-V2-Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • 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: 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

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Haiku 4.5 does not fit this workload in one request. MiMo-V2-Pro has no comparable published API token rate.

    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.

Shared results
1
Claude Haiku 4.5 only
9
MiMo-V2-Pro only
3
Like-for-like categories
0 / 8

2 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
Claude Haiku 4.5
27.4
Supported · #144/152
MiMo-V2-Pro
55.3
Estimated · #41/152
Basis
BenchAlign lane · 4 vs 1 public rows
Reading
Directional only

Knowledge

Directional only
Claude Haiku 4.5
44.3
Estimated · #115/183
MiMo-V2-Pro
53.5
Estimated · #63/183
Basis
BenchAlign lane · 2 vs 0 public rows
Reading
Directional only

Agentic

Not comparable
Claude Haiku 4.5
27.0
Supported · #143/153
MiMo-V2-Pro
Not ranked
Basis
BenchAlign lane · 2 vs 3 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Haiku 4.5
Not ranked
MiMo-V2-Pro
67.9
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Haiku 4.5
28.9
Unranked · 2 rankable rows
MiMo-V2-Pro
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Haiku 4.5
Not ranked
MiMo-V2-Pro
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Haiku 4.5
Not ranked
MiMo-V2-Pro
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Haiku 4.5
Not ranked
MiMo-V2-Pro
84.0
#49/123
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) 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.

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 Haiku 4.5
$0.0035
Fits in one request
MiMo-V2-Pro
API rate not published
Fits in one request

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

Repository review

50K fresh input + 3K output tokens

Claude Haiku 4.5
$0.065
Fits in one request
MiMo-V2-Pro
API rate not published
Fits in one request

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

Cache-heavy agent loop

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

Claude Haiku 4.5
$0.09
Does not fit in one request
MiMo-V2-Pro
API rate not published
Fits in one request
Cached-input rate unavailable

Claude Haiku 4.5 does not fit this workload in one request. MiMo-V2-Pro 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.

Context window

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

Claude Haiku 4.5

200K

Claude API pricing

MiMo-V2-Pro

1M

API model ID

Claude Haiku 4.5

claude-haiku-4-5-20251001

Claude API pricing

MiMo-V2-Pro

Not sourced

Cached-input rate

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

Claude Haiku 4.5

$0.1 per 1M cached input tokens

Claude API pricing

MiMo-V2-Pro

No comparable hosted API rate

Documented inputs

Claude Haiku 4.5

Not sourced

MiMo-V2-Pro

Not sourced

Documented outputs

Claude Haiku 4.5

Not sourced

MiMo-V2-Pro

Not sourced

Provider availability

Claude Haiku 4.5

Not sourced

MiMo-V2-Pro

Not sourced

Reasoning profile

Claude Haiku 4.5

Non-Reasoning

MiMo-V2-Pro

Reasoning

Weight access

Claude Haiku 4.5

Proprietary

MiMo-V2-Pro

Proprietary

License

Claude Haiku 4.5

Proprietary

MiMo-V2-Pro

Proprietary

Release date

Claude Haiku 4.5

2025-10-15

MiMo-V2-Pro

2026-03-18

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-Pro has the higher public score estimate, 62.79 versus 52.91, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
MiMo-V2-Pro has the larger documented window (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 evidence13 rows

Agentic

  • JobBench

    Claude Haiku 4.516.0%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Haiku 4.543.8%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Claw-Eval

    Claude Haiku 4.5—
    MiMo-V2-Pro57.8%
    Source

    Not directly comparable

  • Gert Labs

    Claude Haiku 4.5—
    MiMo-V2-Pro36.68%
    Source

    Not directly comparable

  • ResearchClawBench

    Claude Haiku 4.5—
    MiMo-V2-Pro15.3%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Haiku 4.573.3%
    Source
    MiMo-V2-Pro78%
    Source

    MiMo-V2-Pro leads this result

  • VulcanBench v3

    Claude Haiku 4.576.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Haiku 4.541.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • SWE-bench (Vals)

    Claude Haiku 4.566.6%
    Source
    MiMo-V2-Pro—

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Claude Haiku 4.572.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Haiku 4.578.7%
    Source
    MiMo-V2-Pro—

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Claude Haiku 4.55.903%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Haiku 4.52.083%
    Source
    MiMo-V2-Pro—

    Not directly comparable

Frequently asked questions

Which is better, Claude Haiku 4.5 or MiMo-V2-Pro?

MiMo-V2-Pro has the higher public score estimate, 62.79 versus 52.91, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Haiku 4.5 or MiMo-V2-Pro?

MiMo-V2-Pro scores higher for coding on the public lane, 55.3 to 27.4. 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, Claude Haiku 4.5 or MiMo-V2-Pro?

MiMo-V2-Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Haiku 4.5 or MiMo-V2-Pro?

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 Haiku 4.5 or MiMo-V2-Pro?

MiMo-V2-Pro has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 15, 2026

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