Command A+ vs dots3-note Preview

Updated September 28, 2026. Rank says dots3-note Preview is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

dots3-note Preview has the higher public score, 62.64 versus 36.08, and the 90% score intervals do not overlap. 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

Command A+

Cohere

36.08/100

Estimated · Public rank #130

90% interval 24.6–47.6

Model B

dots3-note Preview

Dots Studio

62.64/100

Estimated · Public rank #36

90% interval 52.8–72.5

Shared results: 1
Command A+ only: 4
dots3-note Preview only: 30
Like-for-like categories: 0 / 8

Estimated: Command A+ and dots3-note PreviewHow 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.

Long documents
Prompts that approach the documented context limit
dots3-note Preview
dots3-note Preview 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
Dots3-note Preview is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Command A+ and dots3-note Preview are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
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. Command A+ does not fit this workload in one request. Command A+ has no published cached-input rate, so cached tokens use its listed input rate. dots3-note Preview 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

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.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

26.0Command A+—dots3-note Preview

Not comparable · BenchAlign v5.7

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

MMMU-ProMultimodal
Normalized gap 16.1
Command A+:63%
dots3-note Preview:79.1%
Command A+ source dots3-note Preview source

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 v5.7 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.

Agentic

Directional only

Command A+: 19.1; Estimated · #95/111
dots3-note Preview: 56.2; Estimated · #25/111
Basis: BenchAlign v5.7 lane · 2 vs 9 public rows
Reading: Directional only

Instruction following

Directional only

Command A+: 89.2; #21/124
dots3-note Preview: 85.2; #37/124
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Directional only

Coding

Not comparable

Command A+: 26.0; Estimated · #99/136
dots3-note Preview: Not ranked
Basis: BenchAlign v5.7 lane · 0 vs 7 public rows
Reading: Not comparable

Reasoning

Not comparable

Command A+: 58.5; Unranked · 2 rankable rows
dots3-note Preview: 72.9; Unranked · 1 rankable row
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Command A+: 16.1; #49/50
dots3-note Preview: 67.2; Unranked · 10 rankable rows
Basis: Provisional lane · 2 vs 1 weighted rows
Reading: Not comparable

Knowledge

Not comparable

Command A+: 29.2; Estimated · #140/160
dots3-note Preview: Not ranked
Basis: BenchAlign v5.7 lane · 0 vs 1 public rows
Reading: Not comparable

Multilingual

Not comparable

Command A+: Not ranked
dots3-note Preview: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Command A+: Not ranked
dots3-note Preview: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Command A+ and dots3-note Preview
Category	Command A+	dots3-note Preview	Basis	Reading
Agentic	19.1Estimated · #95/111	56.2Estimated · #25/111	Directional onlyBenchAlign v5.7 lane · 2 vs 9 public rows	Directional only
Instruction following	89.2#21/124	85.2#37/124	Directional onlyProvisional lane · 0 vs 1 weighted rows	Directional only
Coding	26.0Estimated · #99/136	Not ranked	Not comparableBenchAlign v5.7 lane · 0 vs 7 public rows	Not comparable
Reasoning	58.5Unranked · 2 rankable rows	72.9Unranked · 1 rankable row	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	16.1#49/50	67.2Unranked · 10 rankable rows	Not comparableProvisional lane · 2 vs 1 weighted rows	Not comparable
Knowledge	29.2Estimated · #140/160	Not ranked	Not comparableBenchAlign v5.7 lane · 0 vs 1 public rows	Not comparable
Multilingual	Not ranked	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 v5.7) 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.

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

Command A+: $0.0075; Fits in one request
dots3-note Preview: Self-hosted; infrastructure cost varies; Fits in one request

dots3-note Preview has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Command A+: $0.155; Fits in one request
dots3-note Preview: Self-hosted; infrastructure cost varies; Fits in one request

dots3-note Preview has no comparable published API token rate.

Cache-heavy agent loop

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

Command A+: $0.65; Does not fit in one request; Cached input priced at the published list-input rate
dots3-note Preview: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable

Command A+ does not fit this workload in one request. Command A+ has no published cached-input rate, so cached tokens use its listed input rate. dots3-note Preview 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.

SpecificationCommand A+dots3-note Preview

Context window

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

Command A+

128K

dots3-note Preview

512K

dots3-note Preview model card

API model ID

Command A+

Not sourced

dots3-note Preview

Not sourced

Cached-input rate

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

Command A+

Not published

dots3-note Preview

No comparable hosted API rate

dots3-note Preview model card

Documented inputs

Command A+

Not sourced

dots3-note Preview

Not sourced

Documented outputs

Command A+

Not sourced

dots3-note Preview

Not sourced

Provider availability

Command A+

Not sourced

dots3-note Preview

Not sourced

Reasoning profile

Command A+

Reasoning

dots3-note Preview

Reasoning

Weight access

Command A+

Open Weight

dots3-note Preview

Open Weight

License

Command A+

Open Weight

dots3-note Preview

Open Weight

Release date

Command A+

2026-05-20

dots3-note Preview

2026-08-14

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: dots3-note Preview has the higher public score, 62.64 versus 36.08, and the 90% score intervals do not overlap.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: dots3-note Preview has the larger documented window (512K).

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Command A+ or dots3-note Preview?

dots3-note Preview has the higher public score, 62.64 versus 36.08, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Command A+ or dots3-note Preview?

Dots3-note Preview is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Command A+ or dots3-note Preview?

dots3-note Preview scores higher for agentic tasks on the public lane, 56.2 to 19.1. Command A+ and dots3-note Preview are 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, Command A+ or dots3-note Preview?

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, Command A+ or dots3-note Preview?

dots3-note Preview has the larger documented context window: 512K, compared with 128K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence35 rows

Agentic

τ²-bench results
Command A+85%
Source
dots3-note Preview—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Command A+17.6%
Source
dots3-note Preview—
Not directly comparable
Claw-Eval
Command A+—
dots3-note Preview73.4%
Source
Not directly comparable
Terminal-Bench 2.1
Command A+—
dots3-note Preview75.1%
Source
Not directly comparable
Toolathlon-Verified
Command A+—
dots3-note Preview55.6%
Source
Not directly comparable
skillsBench
Command A+—
dots3-note Preview52.8%
Source
Not directly comparable
APEX-Agents
Command A+—
dots3-note Preview30.8%
Source
Not directly comparable
BrowseComp
Command A+—
dots3-note Preview83.3%
Source
Not directly comparable
HLE w/ tools
Command A+—
dots3-note Preview52.6%
Source
Not directly comparable
DeepSearchQA
Command A+—
dots3-note Preview92.1%
Source
Not directly comparable
WideResearch
Command A+—
dots3-note Preview78.9%
Source
Not directly comparable

Coding

Codeforces
Command A+—
dots3-note Preview3056.0
Source
Not directly comparable
LiveCodeBench v6
Command A+—
dots3-note Preview91.5%
Source
Not directly comparable
Terminal-Bench 2.1
Command A+—
dots3-note Preview75.1%
Source
Not directly comparable
SWE-bench Verified
Command A+—
dots3-note Preview78.4%
Source
Not directly comparable
SWE Multilingual
Command A+—
dots3-note Preview75.7%
Source
Not directly comparable
SWE-bench Pro
Command A+—
dots3-note Preview61%
Source
Not directly comparable
NL2Repo
Command A+—
dots3-note Preview49.8%
Source
Not directly comparable

Reasoning

ARC-AGI-2
Command A+—
dots3-note Preview81.4%
Source
Not directly comparable

Multimodal

MMMU
Command A+75.1%
Source
dots3-note Preview—
Not directly comparable
MMMU-Pro
Command A+63%
Source
dots3-note Preview79.1%
Source
dots3-note Preview leads this result
CharXiv
Command A+52.7%
Source
dots3-note Preview—
Not directly comparable
SimpleVQA
Command A+—
dots3-note Preview72.5%
Source
Not directly comparable
MathVision
Command A+—
dots3-note Preview87.7%
Source
Not directly comparable
ZeroBench
Command A+—
dots3-note Preview19.0%
Source
Not directly comparable
CharXiv w/o tools
Command A+—
dots3-note Preview83.1%
Source
Not directly comparable
GDP.pdf (no tools)
Command A+—
dots3-note Preview60.7%
Source
Not directly comparable
PerceptionBench
Command A+—
dots3-note Preview53.4%
Source
Not directly comparable
BabyVision
Command A+—
dots3-note Preview50.0%
Source
Not directly comparable
MMVU
Command A+—
dots3-note Preview79.9%
Source
Not directly comparable
VideoMMMU
Command A+—
dots3-note Preview86.8%
Source
Not directly comparable

Knowledge

HLE
Command A+—
dots3-note Preview52.6%
Source
Not directly comparable

Instruction following

IFBench
Command A+—
dots3-note Preview80.4%
Source
Not directly comparable
IFEval
Command A+—
dots3-note Preview93.9%
Source
Not directly comparable

Math

IMOAnswerBench
Command A+—
dots3-note Preview90.9%
Source
Not directly comparable

35 public results · 1 shared

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Last updated September 28, 2026

Command A+ vs dots3-note Preview

Decision reading

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Instruction following

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Command A+ or dots3-note Preview?

Which is better for coding, Command A+ or dots3-note Preview?

Which is better for agentic tasks, Command A+ or dots3-note Preview?

Which costs less, Command A+ or dots3-note Preview?

Which has the larger context window, Command A+ or dots3-note Preview?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Math

Related comparisons

Watch Command A+ vs dots3-note Preview