Skip to main content
Radar

Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.

See the free Radar Brief
Anthropic logo
Model A
Claude 4 Sonnet

Anthropic

41.9/100

Supported · Public rank #197

90% interval 38.545.3

Claude 4 Sonnet vs MiMo-V2-Flash

Updated September 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Xiaomi logo
Model B
MiMo-V2-Flash

Xiaomi

53.36/100

Supported · Public rank #122

90% interval 38.068.7

Decision reading

MiMo-V2-Flash has the higher public score estimate, 53.36 versus 41.9, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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

    MiMo-V2-Flash

    MiMo-V2-Flash leads on the same 1 weighted benchmark row.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    MiMo-V2-Flash

    MiMo-V2-Flash has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls
  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    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 4 Sonnet does not fit this workload in one request. Claude 4 Sonnet has no published cached-input rate, so cached tokens use its listed input rate. MiMo-V2-Flash has no comparable published API token rate.

    Confidence: rate-fallback

  • 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 4 Sonnet only
2
MiMo-V2-Flash only
3
Like-for-like categories
1 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Coding

Like-for-like
Claude 4 Sonnet
72.7
MiMo-V2-Flash
73.4
Weighted basis
1 vs 1 rows
Reading
MiMo-V2-Flash leads

Agentic

Not comparable
Claude 4 Sonnet
Not measured
MiMo-V2-Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude 4 Sonnet
Not measured
MiMo-V2-Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Claude 4 Sonnet
Not measured
MiMo-V2-Flash
84.7
Weighted basis
0 vs 2 rows
Reading
Not comparable

Math

Not comparable
Claude 4 Sonnet
Not measured
MiMo-V2-Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude 4 Sonnet
Not measured
MiMo-V2-Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude 4 Sonnet
Not measured
MiMo-V2-Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude 4 Sonnet
Not measured
MiMo-V2-Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

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 4 Sonnet
$0.0105
Fits in one request
MiMo-V2-Flash
Self-hosted; infrastructure cost varies
Fits in one request

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

Repository review

50K fresh input + 3K output tokens

Claude 4 Sonnet
$0.195
Fits in one request
MiMo-V2-Flash
Self-hosted; infrastructure cost varies
Fits in one request

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

Cache-heavy agent loop

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

Claude 4 Sonnet
$0.81
Does not fit in one request
Cached input priced at the published list-input rate
MiMo-V2-Flash
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Claude 4 Sonnet does not fit this workload in one request. Claude 4 Sonnet has no published cached-input rate, so cached tokens use its listed input rate. MiMo-V2-Flash 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 4 Sonnet

200K

MiMo-V2-Flash

256K

API model ID

Claude 4 Sonnet

Not sourced

MiMo-V2-Flash

Not sourced

Cached-input rate

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

Claude 4 Sonnet

Not published

MiMo-V2-Flash

No comparable hosted API rate

Documented inputs

Claude 4 Sonnet

Not sourced

MiMo-V2-Flash

Not sourced

Documented outputs

Claude 4 Sonnet

Not sourced

MiMo-V2-Flash

Not sourced

Provider availability

Claude 4 Sonnet

Not sourced

MiMo-V2-Flash

Not sourced

Reasoning profile

Claude 4 Sonnet

Non-Reasoning

MiMo-V2-Flash

Reasoning

Weight access

Claude 4 Sonnet

Proprietary

MiMo-V2-Flash

Open Weight

License

Claude 4 Sonnet

Proprietary

MiMo-V2-Flash

Open Weight

Release date

Claude 4 Sonnet

2025-05-01

MiMo-V2-Flash

2026-03-15

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-Flash has the higher public score estimate, 53.36 versus 41.9, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
MiMo-V2-Flash has the larger documented window (256K).

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 evidence6 rows

Agentic

  • Gert Labs

    Claude 4 Sonnet39.66%
    Source
    MiMo-V2-Flash

    Not directly comparable

  • JobBench

    Claude 4 Sonnet18.4%
    Source
    MiMo-V2-Flash

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude 4 Sonnet72.7%
    Source
    MiMo-V2-Flash73.4%
    Source

    MiMo-V2-Flash leads this result

Knowledge

  • GPQA

    Claude 4 Sonnet
    MiMo-V2-Flash83.7%
    Source

    Not directly comparable

  • MMLU-Pro

    Claude 4 Sonnet
    MiMo-V2-Flash84.9%
    Source

    Not directly comparable

Math

  • AIME 2025

    Claude 4 Sonnet
    MiMo-V2-Flash94.1%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude 4 Sonnet or MiMo-V2-Flash?

MiMo-V2-Flash has the higher public score estimate, 53.36 versus 41.9, 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 4 Sonnet or MiMo-V2-Flash?

MiMo-V2-Flash leads the like-for-like coding comparison across 1 shared weighted benchmark row.

Which is better for agentic tasks, Claude 4 Sonnet or MiMo-V2-Flash?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude 4 Sonnet or MiMo-V2-Flash?

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 4 Sonnet or MiMo-V2-Flash?

MiMo-V2-Flash has the larger documented context window: 256K, compared with 200K.

Related comparisons

Last updated September 3, 2026

Watch Claude 4 Sonnet vs MiMo-V2-Flash

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.