Llama 3.1-8B: benchmark scores, price and ranking

Llama 3.1-8B from Meta AI ranks #595 of 743 LLMs on the LLMs Tiger aggregate benchmark score (45.3), based on 2 benchmark results captured up to 2026-10-13.

Organisation: Meta AI
Type: Open-weight / local model
Open weights: Yes
Released: 2024-07-23 (source: epoch)
Cheapest API price: $0.030 in / $0.050 out per million tokens (via llamagate, observed 2026-10-13T20:47Z)
Aggregate rank: #595 of 743 (score 45.3)

Across the 2 benchmarks where at least ten models are scored, Llama 3.1-8B is in the top 10% on 0 and in the top half on 0.

Its cheapest listed input price, $0.030 per million tokens, is lower than that of 96% of the 427 models with a listed price.

Llama 3.1-8B benchmark results

Llama 3.1-8B benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
Epoch ECI	117	#142 of 204	Epoch AI Benchmarking Hub	2026-10-13
MMLU-Pro	36.6%	#109 of 136	HuggingFace MMLU-Pro leaderboard	2026-10-13

About Llama 3.1-8B

Llama 3.1-8B is an open-weight model that can run on your own hardware from Meta AI. It was released on 2024-07-23, according to Epoch AI. The cheapest API listing we track charges $0.030 per million input tokens and $0.050 per million output tokens, through llamagate. We hold 2 benchmark results for it across 2 areas, and none is in the top tenth of its board.

Where Llama 3.1-8B stands

On our aggregate score, Llama 3.1-8B is #595 of 743 ranked models, in the lower half. Its score is 45.3; the scale is centred on 50, so it sits 4.7 points below the typical model. That beats 20% of the ranked field. Among the 28 ranked Meta AI models it is #15. The next one up is Llama 4 Maverick (FP8) at 45.6. The next one down is Llama-2-13b-chat at 45.3.

Llama 3.1-8B, benchmark by benchmark

Llama 3.1-8B lands below the middle on Epoch ECI: 117, #142 of 204, with 69% of the field scoring higher. Qwen 3.8 Max leads at 156; the closest result above is Gemini 1.0 Pro at 117. It covers Epoch Capabilities Index: Epoch's own aggregate of ~40 benchmarks. The board median is 127, so Llama 3.1-8B is 11 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

MMLU-Pro is a weak spot. Llama 3.1-8B scores 36.6%, #109 of 136, behind 79% 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 3.1-8B is 18.7 points below it. Source: HuggingFace MMLU-Pro leaderboard, captured 2026-10-13.

Strengths and weaknesses

Llama 3.1-8B 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 3.1-8B 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 nvidia.nemotron-nano-9b-v2 ($0.040) and Mellum2-12B-A2.5B-Instruct ($0.050).

Release history

The Meta AI model released before it was Llama-3.1-70B-Instruct on 2024-07-23, which scores 42.6. The next one was Llama-3.1-8B-Instruct on 2024-07-23, at 36.7.

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

#592 Devstral Small 2 (45.4)
#593 Command R+ (45.4)
#594 Qwen2.5-Coder-1.5B-Instruct (45.4)
#596 Llama-2-13b-chat (45.3)
#597 WizardLM-2-8x22B (45.3)
#598 c4ai-command-r7b-12-2024 (45.3)