Enter opens the highlighted result. Esc closes.

Llama 3.2 3B Instruct vs Solar Pro 4

Solar Pro 4 leads Llama 3.2 3B Instruct on the Artificial Analysis Intelligence Index, 28.2 to 5.7, and Llama 3.2 3B Instruct costs 1.8x less per output token ($0.3325 vs $0.60 per million). Updated October 21, 2026; 27 benchmarks have a result for both.

Replace Llama 3.2 3B Instruct Replace Solar Pro 4
Llama 3.2 3B InstructMeta Llama
Coding
No data
Overall
No data
Output $/M
$0.3325
0
Solar Pro 4Upstage
Coding
No data
Overall
No data
Output $/M
$0.60
27
vs boards won of 27 shared

Llama 3.2 3B Instruct or Solar Pro 4: which to pick

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

Pick Llama 3.2 3B Instruct for output tokens 1.8x cheaper ($0.3325 vs $0.60 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model ALlama 3.2 3B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved taskModel BSolar Pro 4UpstageNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
27
Llama 3.2 3B Instruct only
8
Solar Pro 4 only
18
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
Llama 3.2 3B Instruct not benchmarked, Solar Pro 4 not benchmarked.
Widest category
Coding, 55.6 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: Chinese: Llama 3.2 3B Instruct 1017 against Solar Pro 4 1422, 67.5 points apart on a 0 to 100 scale.
Output price
Llama 3.2 3B Instruct $0.3325 against Solar Pro 4 $0.60 per million output tokens, 1.8x apart.
Context window
Llama 3.2 3B Instruct takes 131K tokens, Solar Pro 4 524K.

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
CategoryLlama 3.2 3B InstructBarsSolar Pro 4Ties
Coding02
Intelligence01
Reasoning05
Math02
Knowledge04
General013
All shared boards027
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
LMArena WebDevNot measured1371Only Solar Pro 4 measured
AA Coding IndexNot measured52.7Only Solar Pro 4 measured
LiveCodeBench (Artificial Analysis run)8.3%Not measuredOnly Llama 3.2 3B Instruct measured
SciCodeNot measured48.0%Only Solar Pro 4 measured
ALE-BenchNot measured179.3Only Solar Pro 4 measured
LMArena Text: coding10981438Solar Pro 4
LMArena Text: software and IT11031431Solar Pro 4
LMArena WebDev: ReactNot measured1363Only Solar Pro 4 measured
LMArena WebDev: HTMLNot measured1371Only Solar Pro 4 measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
AA Intelligence Index5.728.2Solar Pro 4
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Agentic work benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
Design Arena: agents building web appsNot measured1105Only Solar Pro 4 measured
τ²-Bench Telecom21.1%Not measuredOnly Llama 3.2 3B Instruct measured
BALROG10.1%Not measuredOnly Llama 3.2 3B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)21.9%Not measuredOnly Llama 3.2 3B Instruct measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
GPQA Diamond (Artificial Analysis run)25.5%89.1%Solar Pro 4
Humanity's Last Exam (Artificial Analysis run)5.3%29.8%Solar Pro 4
LMArena Text: hard prompts10951400Solar Pro 4
LMArena Text: expert10901428Solar Pro 4
LMArena Text: hard prompts in English11411427Solar Pro 4
Neither model has a result on the other 17 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
AA Math Index3.3Not measuredOnly Llama 3.2 3B Instruct measured
AIME 2025 (Artificial Analysis run)3.3%Not measuredOnly Llama 3.2 3B Instruct measured
LMArena Text: math11261421Solar Pro 4
LMArena Text: mathematical work11281427Solar Pro 4
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
MMLU Pro (Artificial Analysis run)34.7%Not measuredOnly Llama 3.2 3B Instruct measured
LMArena Text: science11061404Solar Pro 4
LMArena Text: medicine and healthcare11041374Solar Pro 4
LMArena Text: legal and government11151383Solar Pro 4
LMArena Text: business and finance10741381Solar Pro 4
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
Design Arena: websitesNot measured1176Only Solar Pro 4 measured
Design Arena: UI componentsNot measured1150Only Solar Pro 4 measured
Design Arena: game devNot measured1170Only Solar Pro 4 measured
Design Arena: data vizNot measured1177Only Solar Pro 4 measured
Design Arena: 3DNot measured1178Only Solar Pro 4 measured
Design Arena: all code categoriesNot measured1182Only Solar Pro 4 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index013
General benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
IFBench26.2%Not measuredOnly Llama 3.2 3B Instruct measured
Long context reasoning (AA-LCR)4.3%70.7%Solar Pro 4
LMArena Text11101388Solar Pro 4
LMArena Text: instruction following10891375Solar Pro 4
LMArena Text: creative writing10941317Solar Pro 4
LMArena Text: English11801414Solar Pro 4
LMArena Text: non-English10191363Solar Pro 4
LMArena Text: Chinese10171422Solar Pro 4
LMArena Text: German10561358Solar Pro 4
LMArena Text: JapaneseNot measured1320Only Solar Pro 4 measured
LMArena Text: KoreanNot measured1383Only Solar Pro 4 measured
LMArena Text: FrenchNot measured1400Only Solar Pro 4 measured
LMArena Text: SpanishNot measured1409Only Solar Pro 4 measured
LMArena Text: Russian9491357Solar Pro 4
LMArena Text: PolishNot measured1304Only Solar Pro 4 measured
LMArena Text: multi-turn11051385Solar Pro 4
LMArena Text: longer queries11001382Solar Pro 4
LMArena Text: writing and language10961344Solar Pro 4
LMArena Text: entertainment and media10831332Solar Pro 4
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Llama 3.2 3B Instruct and Solar Pro 4
BenchmarkLlama 3.2 3B InstructSolar Pro 4Leader
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

Llama 3.2 3B Instruct$0.0002Fits in one request
Solar Pro 4$0.0004Fits in one request

Llama 3.2 3B Instruct costs less

Repository review

50K input + 3K output tokens

Llama 3.2 3B Instruct$0.0035Fits in one request
Solar Pro 4$0.0093Fits in one request

Llama 3.2 3B Instruct costs less

Agent loop

200K input + 10K output tokens

Llama 3.2 3B Instruct$0.013Exceeds the context window
Solar Pro 4$0.036Fits in one request

Llama 3.2 3B Instruct 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 Llama 3.2 3B Instruct and Solar Pro 4
SpecificationMeta Llama 3.2 3B InstructUpstage Solar Pro 4
MakerMeta LlamaUpstage
WeightsOpen weightsNo public weights listed
ReleasedSeptember 25, 2024August 10, 2026
Context window131K524K
Input $/Mtok$0.0505$0.15
Output $/Mtok$0.3325$0.60
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.2 3B Instruct better than Solar Pro 4 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.2 3B Instruct for output tokens 1.8x cheaper ($0.3325 vs $0.60 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Llama 3.2 3B Instruct or Solar Pro 4?

Llama 3.2 3B Instruct costs $0.0505 per million input tokens and $0.3325 per million output tokens; Solar Pro 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.2 3B Instruct or Solar Pro 4?

Solar Pro 4, with 524K tokens against 131K.

How many benchmarks is the Llama 3.2 3B Instruct vs Solar Pro 4 comparison based on?

27 benchmarks have a result for both models as of October 21, 2026. Llama 3.2 3B Instruct's coding index rests on 0 independent benchmarks and Solar Pro 4's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next