Llama 3.2 1B: benchmark scores, price and ranking

Llama 3.2 1B from Meta AI ranks #713 of 743 LLMs on the LLMs Tiger aggregate benchmark score (42.0), based on 2 benchmark results captured up to 2026-10-13.

Organisation: Meta AI
Type: Open-weight / local model
Open weights: Yes
Released: 2024-09-24 (source: epoch)
Cheapest API price: $0.100 in / $0.100 out per million tokens (via vercel_ai_gateway, observed 2026-10-13T20:47Z)
Aggregate rank: #713 of 743 (score 42.0)

Across the 2 benchmarks where at least ten models are scored, Llama 3.2 1B is in the top 10% on 0 and in the top half on 0.

Its cheapest listed input price, $0.100 per million tokens, is lower than that of 79% of the 427 models with a listed price.

Llama 3.2 1B benchmark results

Llama 3.2 1B benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
Epoch ECI	102	#177 of 204	Epoch AI Benchmarking Hub	2026-10-13
MMLU-Pro	11.9%	#134 of 136	HuggingFace MMLU-Pro leaderboard	2026-10-13

About Llama 3.2 1B

Llama 3.2 1B is an open-weight model that can run on your own hardware from Meta AI. It was released on 2024-09-24, according to Epoch AI. The cheapest API listing we track charges $0.100 per million input tokens and $0.100 per million output tokens, through vercel_ai_gateway. We hold 2 benchmark results for it across 2 areas, and none is in the top tenth of its board.

Where Llama 3.2 1B stands

On our aggregate score, Llama 3.2 1B is #713 of 743 ranked models, in the lower half. Its score is 42.0; the scale is centred on 50, so it sits 8.0 points below the typical model. That beats 4% of the ranked field. Among the 28 ranked Meta AI models it is #22. The next one up is Meta-Llama-3-70B-Instruct at 42.5. The next one down is Llama 4 Maverick at 42.0.

Llama 3.2 1B, benchmark by benchmark

Epoch ECI is a weak spot. Llama 3.2 1B scores 102, #177 of 204, behind 86% of the models measured. The leader, Qwen 3.8 Max, reaches 156. It covers Epoch Capabilities Index: Epoch's own aggregate of ~40 benchmarks. The board median is 127, so Llama 3.2 1B is 25 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

MMLU-Pro is a weak spot. Llama 3.2 1B scores 11.9%, #134 of 136, behind 98% of the models measured. The leader, Darwin-180B-RSI, reaches 88.1%. It covers 57-subject knowledge + reasoning. The board median is 55.3%, so Llama 3.2 1B is 43.3 points below it. Source: HuggingFace MMLU-Pro leaderboard, captured 2026-10-13.

Strengths and weaknesses

Llama 3.2 1B has too few results on boards with ten or more models to say where it is strong or weak. Treat any single score as a data point, not a verdict.

Price and value

The median input price across the 427 priced models is $0.500 per million tokens, so Llama 3.2 1B costs less than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on Meta-Llama-3-70B-Instruct ($0.120) and qwen2.5-72b-instruct ($0.120).

Release history

The Meta AI model released before it was Llama-3.2-11B-Vision-Instruct on 2024-09-24, which scores 48.0. The next one was Llama-3.2-1B-Instruct on 2024-09-24, at 41.1.

Reading these numbers

The 2 scores on this page come from 2 sources: Epoch AI Benchmarking Hub (1), HuggingFace MMLU-Pro leaderboard (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 2 results the aggregate rank can move a lot when one new score arrives.

Models ranked nearby

#710 claude-2.0 (42.2)
#711 qwen2.5-72b-instruct (42.2)
#712 granite-3.1-1b-a400m-base (42.1)
#714 SmolLM2-135M (42.0)
#715 SmolLM2-360M (42.0)
#716 gemini-1.5-flash-8b-001 (42.0)