Model comparison

GPT-5.3 Codex vs Llama 3.2 3B

GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 28.9 on the Noometry Index. Llama 3.2 3B costs 40× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.

Last verified October 10, 2026. 0 shared benchmarks.

GPT-5.3 Codex OpenAI

45.8

Rank #69 Reported

Llama 3.2 3B

Summary

The widest gap is in agentic & tool use, where GPT-5.3 Codex leads 48.0 to 20.1.
Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
GPT-5.3 Codex accepts more context: 400K tokens versus 131K.
Llama 3.2 3B has downloadable open weights; the other is API-only.

Side by side

GPT-5.3 Codex and Llama 3.2 3B specifications
	GPT-5.3 Codex	Llama 3.2 3B
Provider	OpenAI	Meta
Noometry Index	45.8	28.9
Released	2026-02-05	2024-09-24
Weights	Proprietary	Open
Context window	400K	131K
Max output	128K	118K
Input $ / M tokens	$1.75	$0.05
Output $ / M tokens	$14	$0.33
Results tracked	8	18

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Category by category

Coding GPT-5.3 Codex leads

GPT-5.3 Codex: 48.6 (#56), Llama 3.2 3B: 27.6 (#319)

Coding benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
SWE-bench Verified	74.8%	—
LMArena WebDev	1409	—
WeirdML	79.3%	—
BigCodeBench Instruct	—	23.4%
LMArena Coding	—	1098
BigCodeBench Complete	—	28.3%
ALE-Bench	1,655	—

Agentic & Tool Use GPT-5.3 Codex leads

GPT-5.3 Codex: 48.0 (#9), Llama 3.2 3B: 20.1 (#143)

Agentic & Tool Use benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
Terminal-Bench	78.4%	—
Berkeley Function Calling Leaderboard	—	21.9%
BALROG	—	10.1%
METR Time Horizons	74.5%	—
Vending-Bench 2	5,940	—

Reasoning Not comparable

GPT-5.3 Codex: —, Llama 3.2 3B: 21.0 (#228)

Reasoning benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
LMArena Hard Prompts	—	1095
Epoch Capabilities Index	156.77	—

Math Not comparable

GPT-5.3 Codex: —, Llama 3.2 3B: 32.4 (#214)

Math benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
LMArena Math	—	1126

Knowledge Not comparable

GPT-5.3 Codex: —, Llama 3.2 3B: 29.7 (#235)

Knowledge benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
LMArena Expert	—	1090

Multilingual Not comparable

GPT-5.3 Codex: —, Llama 3.2 3B: 26.2 (#281)

Multilingual benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
LMArena Non-English	—	1019
LMArena Chinese	—	1017
LMArena German	—	1056
LMArena Russian	—	949

Instruction Following Not comparable

GPT-5.3 Codex: —, Llama 3.2 3B: 56.0 (#275)

Instruction Following benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
LMArena Instruction Following	—	1089

Long Context Not comparable

GPT-5.3 Codex: —, Llama 3.2 3B: 33.4 (#261)

Long Context benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
LMArena Longer Query	—	1100

Writing & Preference Not comparable

GPT-5.3 Codex: —, Llama 3.2 3B: 24.7 (#307)

Writing & Preference benchmarks
Benchmark	GPT-5.3 Codex	Llama 3.2 3B
LMArena Text	—	1110
LMArena Creative Writing	—	1094
EQ-Bench Creative Writing	—	595
LMArena Multi-Turn	—	1105

Frequently asked questions

Is GPT-5.3 Codex better than Llama 3.2 3B?

Which is cheaper, GPT-5.3 Codex or Llama 3.2 3B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.

Is GPT-5.3 Codex or Llama 3.2 3B better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 27.6 in the Noometry coding category.

Which has the bigger context window?

GPT-5.3 Codex does, with 400K tokens against 131K.

How many benchmarks do GPT-5.3 Codex and Llama 3.2 3B share?

0 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Llama 3.2 3B has 18.