Meta: Llama 3.1 8B Instruct
Analysis Summary
Meta's Llama 3.1 8B Instruct is a compact instruction-tuned model with a 131K context window, tool use, and function calling. Its measured reasoning and coding results are limited, while the agentic results are comparatively stronger for its size. Pricing is low at $0.05 per million input tokens and $0.08 per million output tokens.
That combination makes it useful for routing, extraction, structured classification, simple support agents, and high-volume automation where failures can be caught or escalated. The long context helps with larger inputs, but does not compensate for weaker reasoning, coding, and terminal reliability. Use it as a budget workflow component or first-pass model, not for autonomous client operations or polished, unsupervised copy.
Assessed September 7, 2026
Editorial notes
Llama 3.1 8B Instruct is an inexpensive, long-context model with tool use and function calling, useful for routing and lightweight agents, but its measured reasoning and coding capability is limited.
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DFO Verdict
Llama 3.1 8B Instruct is an inexpensive, long-context model with tool use and function calling, useful for routing and lightweight agents, but its measured reasoning and coding capability is limited.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
7.6 Intelligence Index·5.4 Coding Index·8.6 Agentic Index·4.3 Math Index
How Meta: Llama 3.1 8B Instruct compares
Meta: Llama 3.1 8B Instruct ranks #296 of 438 AI models we track for overall intelligence, #198 of 210 for coding, #122 of 192 for agentic tasks. Its 131K-token context window is larger than 47% of the models we list. At $0.05 per million input tokens it is cheaper than 76% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.05 | $0.000050 |
| Output | $0.08 | $0.000080 |
What would Meta: Llama 3.1 8B Instruct cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 779 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Meta: Llama 3.1 8B Instruct for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Meta: Llama 3.1 8B Instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to..
Frequently asked questions about Meta: Llama 3.1 8B Instruct
How much does Meta: Llama 3.1 8B Instruct cost?
Meta: Llama 3.1 8B Instruct costs $0.05 per million input tokens and $0.08 per million output tokens.
What is the context window of Meta: Llama 3.1 8B Instruct?
Meta: Llama 3.1 8B Instruct has a context window of 131,072 tokens (131K).
Is Meta: Llama 3.1 8B Instruct good for coding?
On our coding benchmark index, Meta: Llama 3.1 8B Instruct ranks #198 of 210 models, placing it in the broader range of the field for code generation and debugging.
What can Meta: Llama 3.1 8B Instruct do?
Meta: Llama 3.1 8B Instruct supports tool use and function calling.
Who created Meta: Llama 3.1 8B Instruct?
Meta: Llama 3.1 8B Instruct is developed by Meta and was released on July 23, 2024.