Model comparison

DeepSeek-V3.1 vs Llama 3.2 1B

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 19.9 on the Noometry Index. Llama 3.2 1B costs 6.0× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

Last verified October 10, 2026. 15 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.2

Rank #106 Confirmed

Llama 3.2 1B

Summary

They share 15 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 8 categories and Llama 3.2 1B in 0 categories; 8 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where DeepSeek-V3.1 leads 60.5 to 21.4.
Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.25 / $0.95 for DeepSeek-V3.1.
DeepSeek-V3.1 accepts more context: 164K tokens versus 60K.

Side by side

DeepSeek-V3.1 and Llama 3.2 1B specifications
	DeepSeek-V3.1	Llama 3.2 1B
Provider	DeepSeek	Meta
Noometry Index	42.2	19.9
Released	2025-08-21	2024-09-24
Weights	Open	Open
Context window	164K	60K
Max output	8K	54K
Input $ / M tokens	$0.25	$0.027
Output $ / M tokens	$0.95	$0.20
Results tracked	27	22

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Category by category

Coding DeepSeek-V3.1 leads

DeepSeek-V3.1: 39.8 (#140), Llama 3.2 1B: 20.6 (#333)

Coding benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Coding	1417	1071
WeirdML	38.4%	—
BigCodeBench Instruct	—	8.2%
BigCodeBench Complete	—	11.3%

Agentic & Tool Use Not comparable

DeepSeek-V3.1: —, Llama 3.2 1B: 14.5 (#142)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
Berkeley Function Calling Leaderboard	—	10.8%
BALROG	—	6.6%

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.3 (#109), Llama 3.2 1B: 15.6 (#304)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Hard Prompts	1417	1044
Epoch Capabilities Index	139.92	101.95
SimpleBench	40%	—
Kagi LLM Benchmark	53.2%	—
Chess Puzzles	—	0%
DTBench	82.7%	—
LMCA	24.3%	—
ForecastBench	58	—

Math DeepSeek-V3.1 leads

DeepSeek-V3.1: 36.1 (#125), Llama 3.2 1B: 9.7 (#308)

Math benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Math	1420	1086
OTIS Mock AIME 2024-2025	—	0.6%

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.0 (#86), Llama 3.2 1B: 7.2 (#307)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Expert	1403	1007
GPQA Diamond	—	23.9%
Vectara Hallucination Rate	5.5%	—

Multilingual DeepSeek-V3.1 leads

DeepSeek-V3.1: 51.8 (#100), Llama 3.2 1B: 23.9 (#287)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Non-English	1400	973
LMArena Chinese	1470	958
LMArena German	1412	1014
LMArena Russian	1405	941
LMArena French	1447	—
LMArena Japanese	1374	—
LMArena Korean	1337	—
LMArena Spanish	1429	—

Instruction Following DeepSeek-V3.1 leads

DeepSeek-V3.1: 74.1 (#105), Llama 3.2 1B: 52.6 (#285)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Instruction Following	1400	1031

Long Context DeepSeek-V3.1 leads

DeepSeek-V3.1: 36.3 (#227), Llama 3.2 1B: 31.9 (#269)

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Longer Query	1422	1050
Fiction.LiveBench	52.8%	—

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.5 (#93), Llama 3.2 1B: 21.4 (#305)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Llama 3.2 1B
LMArena Text	1420	1055
LMArena Creative Writing	1401	1033
EQ-Bench Creative Writing	1436	200
LMArena Multi-Turn	1408	1030

Frequently asked questions

Is DeepSeek-V3.1 better than Llama 3.2 1B?

Which is cheaper, DeepSeek-V3.1 or Llama 3.2 1B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; DeepSeek-V3.1 lists at $0.25 and $0.95.

Is DeepSeek-V3.1 or Llama 3.2 1B better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 20.6 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 60K.

How many benchmarks do DeepSeek-V3.1 and Llama 3.2 1B share?

15 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Llama 3.2 1B has 22.