Llama 3.2 3B Instruct vs Perceptron Mk1

Llama 3.2 3B Instruct costs 4.5x less per output token than Perceptron Mk1 ($0.3325 vs $1.50 per million). Updated October 21, 2026; no benchmark has tested both models yet.

Replace Llama 3.2 3B Instruct Replace Perceptron Mk1

Llama 3.2 3B InstructMeta Llama

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

Perceptron Mk1Perceptron

Coding: No data
Overall: No data
Output $/M: $1.50

vs $0.3325 vs $1.50 per 1M output tokens. Llama 3.2 3B Instruct is 4.5x cheaper.

Llama 3.2 3B Instruct or Perceptron Mk1: 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 4.5x cheaper ($0.3325 vs $1.50 per million) and a larger context window (131K against 33K tokens).

Model ALlama 3.2 3B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task Model BPerceptron Mk1PerceptronNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. Llama 3.2 3B Instruct has results on LiveCodeBench (Artificial Analysis run), LMArena Text: coding and LMArena Text: software and IT; Perceptron Mk1 has none yet. Compare them on price and context instead.

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 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.2 3B Instruct
Llama 3.2 3B Instruct $0.0002, Perceptron Mk1 $0.0009 per turn.
List prices

At a glance

Coding index: Llama 3.2 3B Instruct not benchmarked, Perceptron Mk1 not benchmarked.
Widest category: None yet: no category has been tested on both models.
Widest single gap: None yet: no benchmark has tested both models.
Output price: Llama 3.2 3B Instruct $0.3325 against Perceptron Mk1 $1.50 per million output tokens, 4.5x apart.
Context window: Llama 3.2 3B Instruct takes 131K tokens, Perceptron Mk1 33K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards measured

Coding benchmarks for Llama 3.2 3B Instruct and Perceptron Mk1
Benchmark	Llama 3.2 3B Instruct	Perceptron Mk1	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 36 boards here

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured

Intelligence benchmarks for Llama 3.2 3B Instruct and Perceptron Mk1
Benchmark	Llama 3.2 3B Instruct	Perceptron Mk1	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 index3 boards measured

Agentic work benchmarks for Llama 3.2 3B Instruct and Perceptron Mk1
Benchmark	Llama 3.2 3B Instruct	Perceptron Mk1	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
Berkeley Function Calling Leaderboard (BFCL)	21.9%	Not measured	Only Llama 3.2 3B Instruct measured
Neither model has a result on the other 38 boards here

ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured

Reasoning benchmarks for Llama 3.2 3B Instruct and Perceptron Mk1
Benchmark	Llama 3.2 3B Instruct	Perceptron Mk1	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 17 boards here

MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured

Math benchmarks for Llama 3.2 3B Instruct and Perceptron Mk1
Benchmark	Llama 3.2 3B Instruct	Perceptron Mk1	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 measured

Knowledge benchmarks for Llama 3.2 3B Instruct and Perceptron Mk1
Benchmark	Llama 3.2 3B Instruct	Perceptron Mk1	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 13 boards here

GeneralDirectional onlyPublic boards, shown as published, kept out of the index14 boards measured

General benchmarks for Llama 3.2 3B Instruct and Perceptron Mk1
Benchmark	Llama 3.2 3B Instruct	Perceptron Mk1	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

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

Perceptron Mk1$0.0009Fits 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

Perceptron Mk1$0.012Exceeds the context window

Llama 3.2 3B Instruct costs less

Agent loop

200K input + 10K output tokens

Llama 3.2 3B Instruct$0.013Exceeds the context window

Perceptron Mk1$0.045Exceeds 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 Perceptron Mk1
Specification	Meta Llama 3.2 3B Instruct	Perceptron Mk1
Maker	Meta Llama	Perceptron
Weights	Open weights	No public weights listed
Released	September 25, 2024	May 12, 2026
Context window	131K	33K
Input $/Mtok	$0.0505	$0.15
Output $/Mtok	$0.3325	$1.50
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 Perceptron Mk1 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 4.5x cheaper ($0.3325 vs $1.50 per million) and a larger context window (131K against 33K tokens).

Which is cheaper, Llama 3.2 3B Instruct or Perceptron Mk1?

Llama 3.2 3B Instruct costs $0.0505 per million input tokens and $0.3325 per million output tokens; Perceptron Mk1 costs $0.15 and $1.50. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.2 3B Instruct or Perceptron Mk1?

Llama 3.2 3B Instruct, with 131K tokens against 33K.

Has any benchmark tested both Llama 3.2 3B Instruct and Perceptron Mk1?

Llama 3.2 3B Instruct or Perceptron Mk1: which to pick

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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