Llama 3.3 70B Instruct vs MiMo-V2.5-Pro
MiMo-V2.5-Pro leads the LLM Stats Score 25.7 to 13.8. Llama 3.3 70B Instruct is 4.3x cheaper per token.
Meta · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.5-Pro leads the overall LLM Stats Score 25.7 to 13.8, ranking #161 overall.
In the 4 individual benchmarks reported for both models, MiMo-V2.5-Pro wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 3.3 70B Instruct is roughly 4.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5-Pro also accepts a larger context window (1,048,576 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 4.3x cheaper per token
Choose MiMo-V2.5-Pro
- overall performance matters — it scores 25.7 and ranks #161 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for Llama 3.3 70B Instruct · 31 for MiMo-V2.5-Pro
Llama 3.3 70B Instruct outperforms in 1 benchmarks (MMLU-Pro), while MiMo-V2.5-Pro is better at 3 benchmarks (GPQA, MATH, MMLU).
MiMo-V2.5-Pro 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 3.3 70B Instruct ($0.10/1M tokens) is 4.3x cheaper than MiMo-V2.5-Pro ($0.43/1M tokens).
For output processing, Llama 3.3 70B Instruct ($0.20/1M tokens) is 4.3x cheaper than MiMo-V2.5-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.5-Pro is more expensive than Llama 3.3 70B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.5-Pro has 953.2B more parameters than Llama 3.3 70B Instruct, making it 1361.8% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.5-Pro accepts 1,048,576 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 MiMo-V2.5-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.3 Community License Agreement
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Llama 3.3 70B Instruct was released on 2024-12-06, while MiMo-V2.5-Pro was released on 2026-04-27.
MiMo-V2.5-Pro is 17 months newer than Llama 3.3 70B Instruct.
Dec 6, 2024
1.8 years ago
Apr 27, 2026
5 months ago
1.4yr 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. MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita.
Llama 3.3 70B Instruct
MiMo-V2.5-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.3 70B Instruct and MiMo-V2.5-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.3 70B Instruct vs MiMo-V2.5-Pro.