Llama 3.3 70B Instruct vs Mercury 3
Mercury 3 leads the LLM Stats Score 36.1 to 13.3. Llama 3.3 70B Instruct is 1.3x cheaper per token.
Meta · Inception · Updated for 2026
Which is better?
Mercury 3 leads the overall LLM Stats Score 36.1 to 13.3, ranking #98 overall.
In the 1 individual benchmarks reported for both models, Mercury 3 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 3.3 70B Instruct is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mercury 3 also accepts a larger context window (1,000,000 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 3.3 70B Instruct
- cost matters — it's about 1.3x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Mercury 3
- overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
9 reported for Llama 3.3 70B Instruct · 12 for Mercury 3
Llama 3.3 70B Instruct outperforms in 0 benchmarks, while Mercury 3 is better at 1 benchmark (GPQA).
Mercury 3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 3.3 70B Instruct ($0.10/1M tokens) costs the same as Mercury 3 ($0.10/1M tokens).
For output processing, Llama 3.3 70B Instruct ($0.20/1M tokens) is 1.7x cheaper than Mercury 3 ($0.35/1M tokens).
In conclusion, Mercury 3 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
Mercury 3 accepts 1,000,000 input tokens compared to Llama 3.3 70B Instruct's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
Llama 3.3 70B Instruct is licensed under Llama 3.3 Community License Agreement, while Mercury 3 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.3 Community License Agreement
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Llama 3.3 70B Instruct was released on 2024-12-06, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 23 months newer than Llama 3.3 70B Instruct.
Dec 6, 2024
1.9 years ago
Oct 19, 2026
0 days ago
1.9yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 3.3 70B Instruct is available from DeepInfra, Lambda, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks. Mercury 3 is available from Inception.
Llama 3.3 70B Instruct
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.3 70B Instruct and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.3 70B Instruct vs Mercury 3.