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Command A vs Gemma 3 4B

Updated October 21, 2026. 36 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Command ACohere
Coding
No data
Overall
13.1
Output $/M
$10.00
35
Gemma 3 4BGoogle
Coding
No data
Overall
4.8
Output $/M
$0.075
1
vs boards won of 36 shared

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Command A has the edge where the context window is larger, 256K against 131K tokens, and where the benchmark that matters is LMArena Text: medicine and healthcare, where it leads.

Shared results
36
Command A only
24
Gemma 3 4B only
3
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Command A not benchmarked, Gemma 3 4B not benchmarked.
Widest category
Agentic work, 75.7 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Command A 80.7% against Gemma 3 4B 5.0%, 75.7 points apart on a 0 to 100 scale.
Output price
Command A $10.00 against Gemma 3 4B $0.075 per million output tokens, 133.3x apart.
Context window
Command A takes 256K tokens, Gemma 3 4B 131K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryCommand ABarsGemma 3 4BTies
Coding50
Intelligence10
Agentic work10
Reasoning50
Math40
Knowledge41
General150
All shared boards351
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
Coding benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
AA Coding Index27.82.7Command A
LiveCodeBench (Vals AI)35.1%Not measuredOnly Command A measured
SWE-bench Verified (Vals AI)7.8%Not measuredOnly Command A measured
Terminal-Bench 2.1 (Vals AI)17.6%Not measuredOnly Command A measured
LiveCodeBench (Artificial Analysis run)28.7%11.2%Command A
SciCode38.5%Not measuredOnly Command A measured
Terminal-Bench Hard (Artificial Analysis run)25.0%0.8%Command A
LMArena Text: coding13301230Command A
LMArena Text: software and IT13361269Command A
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
AA Intelligence Index13.14.8Command A
Epoch Capabilities IndexNot measured115.9Only Gemma 3 4B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
AA Agentic Index1.0Not measuredOnly Command A measured
Finance Agent (Vals AI)9.0%Not measuredOnly Command A measured
τ²-Bench Telecom80.7%5.0%Command A
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
GPQA Diamond48.5%Not measuredOnly Command A measured
GPQA Diamond (Artificial Analysis run)76.1%29.1%Command A
Humanity's Last Exam (Artificial Analysis run)12.0%5.3%Command A
GPQA Diamond (Epoch AI run)Not measured23.2%Only Gemma 3 4B measured
LMArena Text: hard prompts13261253Command A
LMArena Text: expert12961223Command A
LMArena Text: hard prompts in English13351253Command A
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
AIME13.3%Not measuredOnly Command A measured
MATH 500 (Vals AI)76.2%Not measuredOnly Command A measured
MGSM (Vals AI)85.7%Not measuredOnly Command A measured
AA Math Index13.012.7Command A
AIME 2025 (Artificial Analysis run)13.0%12.7%Command A
OTIS Mock AIMENot measured7.5%Only Gemma 3 4B measured
LMArena Text: math13001239Command A
LMArena Text: mathematical work13121256Command A
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
MMLU Pro69.2%Not measuredOnly Command A measured
LegalBench (Vals AI)79.7%Not measuredOnly Command A measured
CaseLaw (Vals AI)64.5%Not measuredOnly Command A measured
CorpFin (Vals AI)46.0%Not measuredOnly Command A measured
TaxEval (Vals AI)61.4%Not measuredOnly Command A measured
MedQA (Vals AI)80.5%Not measuredOnly Command A measured
MedCode (Vals AI)19.7%Not measuredOnly Command A measured
MMLU Pro (Artificial Analysis run)71.2%41.7%Command A
LMArena Text: science13391306Command A
LMArena Text: medicine and healthcare13341342Gemma 3 4B
LMArena Text: legal and government13481327Command A
LMArena Text: business and finance13151311Command A
Neither model has a result on the other 5 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index150
General benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
MedScribe (Vals AI)55.7%Not measuredOnly Command A measured
IFBench73.9%28.3%Command A
Long context reasoning (AA-LCR)52.7%6.7%Command A
DTBench61.3%50.9%Command A
LMCA10.3%2.8%Command A
LMArena Text13311291Command A
LMArena Text: instruction following13091239Command A
LMArena Text: creative writing13191270Command A
LMArena Text: English13441300Command A
LMArena Text: non-English13131273Command A
LMArena Text: Chinese1327Not measuredOnly Command A measured
LMArena Text: German13421281Command A
LMArena Text: Japanese1285Not measuredOnly Command A measured
LMArena Text: Korean1285Not measuredOnly Command A measured
LMArena Text: French1351Not measuredOnly Command A measured
LMArena Text: Spanish1347Not measuredOnly Command A measured
LMArena Text: Russian13141294Command A
LMArena Text: Polish1324Not measuredOnly Command A measured
LMArena Text: multi-turn13381255Command A
LMArena Text: longer queries13341273Command A
LMArena Text: writing and language13281288Command A
LMArena Text: entertainment and media13061233Command A
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Command A and Gemma 3 4B
BenchmarkCommand AGemma 3 4BLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Command A$0.0075Fits in one request
Gemma 3 4B$0.0001Fits in one request

Gemma 3 4B costs less

Repository review

50K input + 3K output tokens

Command A$0.155Fits in one request
Gemma 3 4B$0.0025Fits in one request

Gemma 3 4B costs less

Agent loop

200K input + 10K output tokens

Command A$0.600Fits in one request
Gemma 3 4B$0.0097Exceeds the context window

Gemma 3 4B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Command A and Gemma 3 4B
SpecificationCohere Command AGoogle Gemma 3 4B
MakerCohereGoogle
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025March 13, 2025
Context window256K131K
Input $/Mtok$2.50$0.045
Output $/Mtok$10.00$0.075
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved task$2.69Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command A better than Gemma 3 4B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Command A has the edge where the context window is larger, 256K against 131K tokens, and where the benchmark that matters is LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, Command A or Gemma 3 4B?

Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Gemma 3 4B costs $0.045 and $0.075. Cost per solved task is known for Command A only.

Which has the bigger context window, Command A or Gemma 3 4B?

Command A, with 256K tokens against 131K.

How many benchmarks is the Command A vs Gemma 3 4B comparison based on?

36 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and Gemma 3 4B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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