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Gemma 3 4B vs Mercury 2

Mercury 2 leads Gemma 3 4B on the Artificial Analysis Intelligence Index, 10.8 to 4.8, and Gemma 3 4B costs 10.0x less per output token ($0.075 vs $0.75 per million). Updated October 21, 2026; 26 benchmarks have a result for both.

Replace Gemma 3 4B Replace Mercury 2
Gemma 3 4BGoogle
Coding
No data
Overall
22.6
Output $/M
$0.075
0
Mercury 2Inception
Coding
No data
Overall
No data
Output $/M
$0.75
26
vs boards won of 26 shared

Gemma 3 4B or Mercury 2: which to pick

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

Pick Gemma 3 4B for output tokens 10.0x cheaper ($0.075 vs $0.75 per million) and a larger context window (131K against 128K tokens).

Model AGemma 3 4BGoogleNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMercury 2InceptionNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
26
Gemma 3 4B only
16
Mercury 2 only
16
Like-for-like categories
6 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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
Gemma 3 4B not benchmarked, Mercury 2 not benchmarked.
Widest category
Agentic work, 65.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemma 3 4B 5.0% against Mercury 2 70.8%, 65.8 points apart on a 0 to 100 scale.
Output price
Gemma 3 4B $0.075 against Mercury 2 $0.75 per million output tokens, 10.0x apart.
Context window
Gemma 3 4B takes 131K tokens, Mercury 2 128K.

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
CategoryGemma 3 4BBarsMercury 2Ties
Coding04
Intelligence01
Agentic work01
Reasoning05
Knowledge03
General012
All shared boards026
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
LMArena WebDevNot measured1171Only Mercury 2 measured
AA Coding Index2.731.1Mercury 2
LiveCodeBench (Artificial Analysis run)11.2%Not measuredOnly Gemma 3 4B measured
SciCodeNot measured37.7%Only Mercury 2 measured
Terminal-Bench Hard (Artificial Analysis run)0.8%26.5%Mercury 2
WeirdMLNot measured43.2%Only Mercury 2 measured
ALE-BenchNot measured785.6Only Mercury 2 measured
LMArena Text: coding12301390Mercury 2
LMArena Text: software and IT12691385Mercury 2
LMArena WebDev: ReactNot measured1160Only Mercury 2 measured
LMArena WebDev: HTMLNot measured1199Only Mercury 2 measured
SciCode0.0%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
AA Intelligence Index4.810.8Mercury 2
Epoch Capabilities Index115.9Not measuredOnly Gemma 3 4B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
AA Agentic IndexNot measured1.6Only Mercury 2 measured
τ²-Bench Telecom5.0%70.8%Mercury 2
Berkeley Function Calling Leaderboard (BFCL)19.6%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
GPQA Diamond (Artificial Analysis run)29.1%77.0%Mercury 2
Humanity's Last Exam (Artificial Analysis run)5.3%17.1%Mercury 2
GPQA Diamond (Epoch AI run)23.2%Not measuredOnly Gemma 3 4B measured
LMArena Text: hard prompts12531362Mercury 2
LMArena Text: expert12231358Mercury 2
LMArena Text: hard prompts in English12531374Mercury 2
Kagi LLM Benchmark25.2%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
AA Math Index12.7Not measuredOnly Gemma 3 4B measured
AIME 2025 (Artificial Analysis run)12.7%Not measuredOnly Gemma 3 4B measured
OTIS Mock AIME7.5%Not measuredOnly Gemma 3 4B measured
LMArena Text: math1239Not measuredOnly Gemma 3 4B measured
LMArena Text: mathematical work1256Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index03
Knowledge benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
MMLU Pro (Artificial Analysis run)41.7%Not measuredOnly Gemma 3 4B measured
LMArena Text: science13061343Mercury 2
LMArena Text: medicine and healthcare13421363Mercury 2
LMArena Text: legal and government1327Not measuredOnly Gemma 3 4B measured
LMArena Text: business and finance13111349Mercury 2
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
Design Arena: websitesNot measured1036Only Mercury 2 measured
Design Arena: UI componentsNot measured998Only Mercury 2 measured
Design Arena: game devNot measured985Only Mercury 2 measured
Design Arena: data vizNot measured1009Only Mercury 2 measured
Design Arena: 3DNot measured983Only Mercury 2 measured
Design Arena: all code categoriesNot measured1022Only Mercury 2 measured
Design Arena: SVGNot measured998Only Mercury 2 measured
Design Arena: ASCII artNot measured988Only Mercury 2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index012
General benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
IFBench28.3%69.8%Mercury 2
Long context reasoning (AA-LCR)6.7%43.7%Mercury 2
DTBench50.9%Not measuredOnly Gemma 3 4B measured
LMCA2.8%Not measuredOnly Gemma 3 4B measured
LMArena Text12911354Mercury 2
LMArena Text: instruction following12391328Mercury 2
LMArena Text: creative writing12701286Mercury 2
LMArena Text: English13001378Mercury 2
LMArena Text: non-English12731330Mercury 2
LMArena Text: ChineseNot measured1414Only Mercury 2 measured
LMArena Text: German1281Not measuredOnly Gemma 3 4B measured
LMArena Text: Russian12941304Mercury 2
LMArena Text: multi-turn12551357Mercury 2
LMArena Text: longer queries12731329Mercury 2
LMArena Text: writing and language12881300Mercury 2
LMArena Text: entertainment and media12331314Mercury 2
Neither model has a result on the other 30 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 3 4B and Mercury 2
BenchmarkGemma 3 4BMercury 2Leader
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

Gemma 3 4B$0.0001Fits in one request
Mercury 2$0.0006Fits in one request

Gemma 3 4B costs less

Repository review

50K input + 3K output tokens

Gemma 3 4B$0.0025Fits in one request
Mercury 2$0.015Fits in one request

Gemma 3 4B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 4B$0.0097Exceeds the context window
Mercury 2$0.058Exceeds 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 Gemma 3 4B and Mercury 2
SpecificationGoogle Gemma 3 4BInception Mercury 2
MakerGoogleInception
WeightsOpen weightsNo public weights listed
ReleasedMarch 13, 2025March 4, 2026
Context window131K128K
Input $/Mtok$0.045$0.25
Output $/Mtok$0.075$0.75
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 4B better than Mercury 2 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 4B for output tokens 10.0x cheaper ($0.075 vs $0.75 per million) and a larger context window (131K against 128K tokens).

Which is cheaper, Gemma 3 4B or Mercury 2?

Gemma 3 4B costs $0.045 per million input tokens and $0.075 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 3 4B or Mercury 2?

Gemma 3 4B, with 131K tokens against 128K.

How many benchmarks is the Gemma 3 4B vs Mercury 2 comparison based on?

26 benchmarks have a result for both models as of October 21, 2026. Gemma 3 4B's coding index rests on 0 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.

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