Llama 3.1 70B Instruct vs Phi 4
Llama 3.1 70B Instruct and Phi 4 are closely matched at 7.6 and 5.4 on the LLM Stats Score. Phi 4 is 2.3x cheaper per token.
Meta · Microsoft · Updated for 2026
Which is better?
Llama 3.1 70B Instruct and Phi 4 are closely matched on the overall LLM Stats Score at 7.6 and 5.4.
In the 6 individual benchmarks reported for both models, Phi 4 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Phi 4 is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 3.1 70B Instruct also accepts a larger context window (128,000 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 70B Instruct
- you process long inputs — it offers a 128,000 token context window
Choose Phi 4
- you value its reported benchmark strengths — it wins 4 of 6 exact shared results
- cost matters — it's about 2.3x cheaper per token
- you want the most recent training data — it shipped Dec 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 70B Instruct · 13 for Phi 4
Llama 3.1 70B Instruct outperforms in 2 benchmarks (DROP, IFEval), while Phi 4 is better at 4 benchmarks (GPQA, HumanEval, MMLU, MMLU-Pro).
Phi 4 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 3.1 70B Instruct ($0.20/1M tokens) is 2.9x more expensive than Phi 4 ($0.07/1M tokens).
For output processing, Llama 3.1 70B Instruct ($0.20/1M tokens) is 1.4x more expensive than Phi 4 ($0.14/1M tokens).
In conclusion, Llama 3.1 70B Instruct is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 3.1 70B Instruct has 55.3B more parameters than Phi 4, making it 376.2% larger.
Context Window
Maximum input and output token capacity
Llama 3.1 70B Instruct accepts 128,000 input tokens compared to Phi 4's 16,384 tokens. Llama 3.1 70B Instruct can generate longer responses up to 128,000 tokens, while Phi 4 is limited to 16,384 tokens.
License
Usage and distribution terms
Llama 3.1 70B Instruct is licensed under Llama 3.1 Community License, while Phi 4 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 70B Instruct was released on 2024-07-23, while Phi 4 was released on 2024-12-12.
Phi 4 is 5 months newer than Llama 3.1 70B Instruct.
Jul 23, 2024
2.2 years ago
Dec 12, 2024
1.8 years ago
4mo newerKnowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Llama 3.1 70B Instruct's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Llama 3.1 70B Instruct's cutoff date.
—
Jun 2024
Provider Availability
Llama 3.1 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Cerebras, Together, Fireworks, Bedrock, Sambanova. Phi 4 is available from DeepInfra.
Llama 3.1 70B Instruct
Phi 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.1 70B Instruct and Phi 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.1 70B Instruct vs Phi 4.