Llama 3.1 70B
Not tested yet
Language modelActive
Llama 3.1 70B
Meta
- Released
- July 2024
- Data date
- September 8, 2026
- Intelligence
- Overall score
- Speed
- 62.6 tokens/sOutput throughput
- Price
- Input · Output / 1M tokens
- Input
- Text
- Output
- Text
No published category-wide ranking is available for this model.
Entries 1-12 of 23. Page 1 of 2.
Measurements without matching peer values
These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.
MMLU instruct (Show measurement, test conditions, and source)
- Source value
- 83.6
- Score
- 83.6
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:0
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table; 5-shot
MMLU CoT (Show measurement, test conditions, and source)
- Source value
- 86
- Score
- 86
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:1
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table; CoT
MMLU Pro instruct (Show measurement, test conditions, and source)
- Source value
- 66.4
- Score
- 66.4
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:2
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table
IFEval (Show measurement, test conditions, and source)
- Source value
- 87.5
- Score
- 87.5
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:3
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table
ARC instruct (Show measurement, test conditions, and source)
- Source value
- 94.8
- Score
- 94.8
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:4
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table
GPQA (Show measurement, test conditions, and source)
- Source value
- 46.7
- Score
- 46.7
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:5
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table
HumanEval (Show measurement, test conditions, and source)
- Source value
- 80.5
- Score
- 80.5
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:6
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table
MBPP (Show measurement, test conditions, and source)
- Source value
- 86
- Score
- 86
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:7
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table
GSM8K (Show measurement, test conditions, and source)
- Source value
- 95.1
- Score
- 95.1
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:8
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table; CoT
MATH (Show measurement, test conditions, and source)
- Source value
- 68
- Score
- 68
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:9
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct table
API-Bank (Show measurement, test conditions, and source)
- Source value
- 90
- Score
- 90
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:10
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct tool-use table
BFCL (Show measurement, test conditions, and source)
- Source value
- 84.8
- Score
- 84.8
- Metric
- percent
- Unit
- %
- Direction
- Higher is better
- Comparison cohort
- research:llama-3.1-70b:11
- Source type
- vendor-reported
- Evaluator
- Meta Llama 3.1 model card
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Instruct tool-use table
Our model tests
Community tests you can inspect
Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.
Pelican on a bicycle
A community classic for free-form SVG drawing.
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)Profile
Specifications and access
Published information about this model. Existing estimates are explicitly labeled.
Additional source observations
Dated documentation and model-card observations. Provider limits, native context and extended context can differ. Configuration notes retain the source wording.
Pricing
Published prices
Prices apply to the stated unit. Resolution, output length, and provider can change the cost.
Cost example
100 API requests
$0.06
100 requests with 1,000 input and 500 output tokens each calculate to $0.06. Input accounts for $0.04; output accounts for $0.02.
- Input price
- $0.4 / 1M tokensBase tier for each request
- Output price
- $0.4 / 1M tokensBase tier for each request
The calculation uses documented token prices and no cache discount. It excludes extra tools, tax, reasoning tokens, and further hidden output tokens.
Open sourceHead-to-head comparisons
Compare this model
Each matchup compares this model with exactly one other model from the same category.
There are no published direct comparisons for this model yet.
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Evidence
Sources and data date
Every statement links to its underlying documentation or leaderboard.
- Speed
Median across serving providers. Output speed after the first streaming chunk, not total response time. Classified as deprecated by Artificial Analysis. Artificial Analysis maintains only the default 10K-input workload there. Retrieved September 8, 2026.
- Price
Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
- Input
Documented modalities. Retrieved September 8, 2026.
- Output
Documented modalities. Retrieved September 8, 2026.
Research date September 8, 2026. 2 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.
Open evidence questions and research notes (original wording)
Not found in the inspected sources
max-output-tokens. No model-specific maximum output in the card.