Llama 3.2 3B Instruct vs Sonar Deep Research

Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Llama 3.2 3B Instruct Replace Sonar Deep Research

Llama 3.2 3B InstructMeta Llama

Coding: No data
Overall: 5.7
Output $/M: $0.3325

Sonar Deep ResearchPerplexity

Coding: No data
Overall: No data
Output $/M: $8.00

vs $0.3325 vs $8.00 per 1M output tokens. Llama 3.2 3B Instruct is 24.1x cheaper.

Decision reading

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

Llama 3.2 3B Instruct has the edge where output tokens cost 24.1x less, and where the context window is larger, 131K against 128K tokens.

Model ALlama 3.2 3B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task Model BSonar Deep ResearchPerplexityNot benchmarkedNo coding benchmarkNo cost per solved task

Shared results: 0
Llama 3.2 3B Instruct only: 34
Sonar Deep Research only: 0
Like-for-like categories: 0 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.

Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Llama 3.2 3B Instruct has a AA Intelligence Index result, 5.7.
Directional only
Long documents
Listed context window
Llama 3.2 3B Instruct
Llama 3.2 3B Instruct takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.2 3B Instruct
Llama 3.2 3B Instruct $0.0002, Sonar Deep Research $0.0060 per turn.
List prices

At a glance

Coding index: Llama 3.2 3B Instruct not benchmarked, Sonar Deep Research not benchmarked.
Widest category: No category has a result for both models.
Widest single gap: No benchmark has a result for both models.
Output price: Llama 3.2 3B Instruct $0.3325 against Sonar Deep Research $8.00 per million output tokens, 24.1x apart.
Context window: Llama 3.2 3B Instruct takes 131K tokens, Sonar Deep Research 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.

CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared

Coding benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
LiveCodeBench (Artificial Analysis run)	8.3%	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: coding	1098	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: software and IT	1103	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 35 boards here

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared

Intelligence benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
AA Intelligence Index	5.7	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 1 board here

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared

Agentic work benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
τ²-Bench Telecom	21.1%	Not measured	Only Llama 3.2 3B Instruct measured
BALROG	10.1%	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 37 boards here

ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared

Reasoning benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
GPQA Diamond (Artificial Analysis run)	25.5%	Not measured	Only Llama 3.2 3B Instruct measured
Humanity's Last Exam (Artificial Analysis run)	5.3%	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: hard prompts	1095	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: expert	1090	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: hard prompts in English	1141	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 16 boards here

MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared

Math benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
AA Math Index	3.3	Not measured	Only Llama 3.2 3B Instruct measured
AIME 2025 (Artificial Analysis run)	3.3%	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: math	1126	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: mathematical work	1128	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 9 boards here

KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared

Knowledge benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
MMLU Pro (Artificial Analysis run)	34.7%	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: science	1106	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: medicine and healthcare	1104	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: legal and government	1115	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: business and finance	1074	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 12 boards here

Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Web design benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
Neither model has a result on 9 boards here

GeneralDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared

General benchmarks for Llama 3.2 3B Instruct and Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
IFBench	26.2%	Not measured	Only Llama 3.2 3B Instruct measured
Long context reasoning (AA-LCR)	4.3%	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text	1110	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: instruction following	1089	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: creative writing	1094	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: English	1180	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: non-English	1019	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: Chinese	1017	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: German	1056	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: Russian	949	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: multi-turn	1105	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: longer queries	1100	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: writing and language	1096	Not measured	Only Llama 3.2 3B Instruct measured
LMArena Text: entertainment and media	1083	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 32 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 Sonar Deep Research
Benchmark	Llama 3.2 3B Instruct	Sonar Deep Research	Leader
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

Sonar Deep Research$0.0060Fits 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

Sonar Deep Research$0.124Fits 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

Sonar Deep Research$0.480Exceeds the context window

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 Sonar Deep Research
Specification	Meta Llama 3.2 3B Instruct	Perplexity Sonar Deep Research
Maker	Meta Llama	Perplexity
Weights	Open weights	No public weights listed
Released	September 25, 2024	March 7, 2025
Context window	131K	128K
Input $/Mtok	$0.0505	$2.00
Output $/Mtok	$0.3325	$8.00
Coding index	Not benchmarked	Not benchmarked
Independent measurements behind it	0	0
Cost per solved task	Not computable	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is Llama 3.2 3B Instruct better than Sonar Deep Research for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Llama 3.2 3B Instruct has the edge where output tokens cost 24.1x less, and where the context window is larger, 131K against 128K tokens.

Which is cheaper, Llama 3.2 3B Instruct or Sonar Deep Research?

Llama 3.2 3B Instruct costs $0.0505 per million input tokens and $0.3325 per million output tokens; Sonar Deep Research costs $2.00 and $8.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.2 3B Instruct or Sonar Deep Research?

Llama 3.2 3B Instruct, with 131K tokens against 128K.

How many benchmarks is the Llama 3.2 3B Instruct vs Sonar Deep Research comparison based on?

0 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 Sonar Deep Research's on 0. Where only one model has a result, the page says so instead of naming a winner.

Decision reading

Which one for your work

Coding

Intelligence

Long documents

Everyday cost

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

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