Llama 3.1 8B Instruct vs Phi-3.5-mini-instruct
Llama 3.1 8B Instruct and Phi-3.5-mini-instruct are closely matched at -2.6 and -3.8 on the LLM Stats Score. Llama 3.1 8B Instruct is 4.4x cheaper per token.
Meta · Microsoft · Updated for 2026
Which is better?
Llama 3.1 8B Instruct and Phi-3.5-mini-instruct are closely matched on the overall LLM Stats Score at -2.6 and -3.8.
In the 5 individual benchmarks reported for both models, Llama 3.1 8B Instruct wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 3.1 8B Instruct is roughly 4.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 3.1 8B Instruct also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Llama 3.1 8B Instruct
- you value its reported benchmark strengths — it wins 3 of 5 exact shared results
- cost matters — it's about 4.4x cheaper per token
- you process long inputs — it offers a 131,072 token context window
Choose Phi-3.5-mini-instruct
- you want the most recent training data — it shipped Aug 2024
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for Llama 3.1 8B Instruct · 31 for Phi-3.5-mini-instruct
Llama 3.1 8B Instruct outperforms in 3 benchmarks (HumanEval, MMLU, MMLU-Pro), while Phi-3.5-mini-instruct is better at 1 benchmark (ARC-C).
Llama 3.1 8B Instruct has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 3.1 8B Instruct ($0.02/1M tokens) is 5.0x cheaper than Phi-3.5-mini-instruct ($0.10/1M tokens).
For output processing, Llama 3.1 8B Instruct ($0.03/1M tokens) is 3.3x cheaper than Phi-3.5-mini-instruct ($0.10/1M tokens).
In conclusion, Phi-3.5-mini-instruct is more expensive than Llama 3.1 8B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 3.1 8B Instruct has 4.2B more parameters than Phi-3.5-mini-instruct, making it 110.5% larger.
Context Window
Maximum input and output token capacity
Llama 3.1 8B Instruct accepts 131,072 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. Llama 3.1 8B Instruct can generate longer responses up to 131,072 tokens, while Phi-3.5-mini-instruct is limited to 128,000 tokens.
License
Usage and distribution terms
Llama 3.1 8B Instruct is licensed under Llama 3.1 Community License, while Phi-3.5-mini-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.1 Community License
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Llama 3.1 8B Instruct was released on 2024-07-23, while Phi-3.5-mini-instruct was released on 2024-08-23.
Phi-3.5-mini-instruct is 1 month newer than Llama 3.1 8B Instruct.
Jul 23, 2024
2.2 years ago
Aug 23, 2024
2.1 years ago
1mo newerKnowledge Cutoff
When training data ends
Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while Phi-3.5-mini-instruct's cutoff date is not specified.
We can confirm Llama 3.1 8B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without Phi-3.5-mini-instruct's cutoff date.
Dec 2023
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Provider Availability
Llama 3.1 8B Instruct is available from DeepInfra, Lambda, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock. Phi-3.5-mini-instruct is available from Azure.
Llama 3.1 8B Instruct
Phi-3.5-mini-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.1 8B Instruct and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.1 8B Instruct vs Phi-3.5-mini-instruct.