Llama 3.1-70B: benchmark scores, price and ranking

Llama 3.1-70B from Meta AI ranks #430 of 743 LLMs on the LLMs Tiger aggregate benchmark score (47.5), 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: $0.720 in / $0.720 out per million tokens (via vercel_ai_gateway, observed 2026-10-13T20:47Z)
Aggregate rank: #430 of 743 (score 47.5)

Across the 2 benchmarks where at least ten models are scored, Llama 3.1-70B is in the top 10% on 0 and in the top half on 0.

Its cheapest listed input price, $0.720 per million tokens, is lower than that of 41% of the 427 models with a listed price.

Llama 3.1-70B benchmark results

Llama 3.1-70B benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
MMLU-Pro	52.5%	#73 of 136	HuggingFace MMLU-Pro leaderboard	2026-10-13
Epoch ECI	126	#110 of 204	Epoch AI Benchmarking Hub	2026-10-13

About Llama 3.1-70B

Llama 3.1-70B 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 $0.720 per million input tokens and $0.720 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 3.1-70B stands

On our aggregate score, Llama 3.1-70B is #430 of 743 ranked models, around the middle of the table. Its score is 47.5; the scale is centred on 50, so it sits 2.5 points below the typical model. That beats 42% of the ranked field. Among the 28 ranked Meta AI models it is #9. The next one up is Llama-3.2-11B-Vision-Instruct at 48.0. The next one down is Llama 4 Scout at 47.4.

Llama 3.1-70B, benchmark by benchmark

Llama 3.1-70B lands below the middle on MMLU-Pro: 52.5%, #73 of 136, with 53% of the field scoring higher. Darwin-180B-RSI leads at 88.1%; the closest result above is Meta-Llama-3-70B at 52.8%. It covers 57-subject knowledge + reasoning. The board median is 55.3%, so Llama 3.1-70B is 2.8 points below it. Source: HuggingFace MMLU-Pro leaderboard, captured 2026-10-13.

Llama 3.1-70B lands below the middle on Epoch ECI: 126, #110 of 204, with 53% of the field scoring higher. Qwen 3.8 Max leads at 156; the closest result above is GPT-4 Turbo (Nov 2023) at 126. It covers Epoch Capabilities Index: Epoch's own aggregate of ~40 benchmarks. The board median is 127, so Llama 3.1-70B is 1 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

Strengths and weaknesses

Llama 3.1-70B 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 3.1-70B costs more 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 Gemini 3.6 Flash (High) ($0.750) and GPT-5.4 mini (xhigh) ($0.750).

Release history

The Meta AI model released before it was Llama-3.1-405B-Instruct on 2024-07-23, which scores 43.6. The next one was Llama-3.1-70B-Instruct on 2024-07-23, at 42.6.

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

#427 Gemini 1.5 Pro (47.5)
#428 GPT-4.5 (47.5)
#429 yi-coder:9b-chat-q4_0 (47.5)
#431 gemini-2.0-flash-exp (47.5)
#432 Gemma 4 26B A4B (47.5)
#433 GPT-5.1 (Thinking, None) (47.5)