Gemini 1.5 Pro vs Llama 3.3 70B Instruct
Gemini 1.5 Pro and Llama 3.3 70B Instruct are closely matched at 12.5 and 14.3 on the LLM Stats Score. Llama 3.3 70B Instruct is 21.9x cheaper per token.
Google · Meta · Updated for 2026
Which is better?
Gemini 1.5 Pro and Llama 3.3 70B Instruct are closely matched on the overall LLM Stats Score at 12.5 and 14.3.
The models split the 6 individual benchmarks reported for both models evenly.
On price, Llama 3.3 70B Instruct is roughly 21.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 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 Gemini 1.5 Pro
- you process long inputs — it offers a 2,097,152 token context window
Choose Llama 3.3 70B Instruct
- cost matters — it's about 21.9x cheaper per token
- you want the most recent training data — it shipped Dec 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
23 reported for Gemini 1.5 Pro · 9 for Llama 3.3 70B Instruct
Gemini 1.5 Pro outperforms in 3 benchmarks (GPQA, MATH, MMLU-Pro), while Llama 3.3 70B Instruct is better at 3 benchmarks (HumanEval, MGSM, MMLU).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 12.5x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 50.0x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than Llama 3.3 70B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Llama 3.3 70B Instruct's 128,000 tokens. Llama 3.3 70B Instruct can generate longer responses up to 128,000 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 1.5 Pro supports multimodal inputs, whereas Llama 3.3 70B Instruct does not.
Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 1.5 Pro
Llama 3.3 70B Instruct
License
Usage and distribution terms
Gemini 1.5 Pro is licensed under a proprietary license, while Llama 3.3 70B Instruct uses Llama 3.3 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.3 Community License Agreement
Open weights
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while Llama 3.3 70B Instruct was released on 2024-12-06.
Llama 3.3 70B Instruct is 7 months newer than Gemini 1.5 Pro.
May 1, 2024
2.3 years ago
Dec 6, 2024
1.7 years ago
7mo newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Llama 3.3 70B Instruct's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Llama 3.3 70B Instruct's cutoff date.
Nov 2023
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Provider Availability
Gemini 1.5 Pro is available from Google. Llama 3.3 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks.
Gemini 1.5 Pro
Llama 3.3 70B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and Llama 3.3 70B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs Llama 3.3 70B Instruct.