GPT OSS 120B vs Llama 3.3 70B Instruct
GPT OSS 120B leads the LLM Stats Score 28.7 to 13.8. GPT OSS 120B is 1.8x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT OSS 120B leads the overall LLM Stats Score 28.7 to 13.8, ranking #138 overall.
In the 2 individual benchmarks reported for both models, GPT OSS 120B wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT OSS 120B is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT OSS 120B
- overall performance matters — it scores 28.7 and ranks #138 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.8x cheaper per token
- you want the most recent training data — it shipped Aug 2025
Choose Llama 3.3 70B Instruct
- you want predictable pricing at $0.10/M input and $0.20/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
7 reported for GPT OSS 120B · 9 for Llama 3.3 70B Instruct
GPT OSS 120B outperforms in 2 benchmarks (GPQA, MMLU), while Llama 3.3 70B Instruct is better at 0 benchmarks.
GPT OSS 120B 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, GPT OSS 120B ($0.04/1M tokens) is 2.7x cheaper than Llama 3.3 70B Instruct ($0.10/1M tokens).
For output processing, GPT OSS 120B ($0.17/1M tokens) is 1.2x cheaper than Llama 3.3 70B Instruct ($0.20/1M tokens).
In conclusion, Llama 3.3 70B Instruct is more expensive than GPT OSS 120B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GPT OSS 120B has 46.8B more parameters than Llama 3.3 70B Instruct, making it 66.9% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
GPT OSS 120B is licensed under Apache 2.0, 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.
Apache 2.0
Open weights
Llama 3.3 Community License Agreement
Open weights
Release Timeline
When each model was launched
GPT OSS 120B was released on 2025-08-05, while Llama 3.3 70B Instruct was released on 2024-12-06.
GPT OSS 120B is 8 months newer than Llama 3.3 70B Instruct.
Aug 5, 2025
1.1 years ago
8mo newerDec 6, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT OSS 120B is available from DeepInfra, Novita, OpenAI, Fireworks, Groq. Llama 3.3 70B Instruct is available from DeepInfra, Lambda, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks.
GPT OSS 120B
Llama 3.3 70B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT OSS 120B and Llama 3.3 70B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT OSS 120B vs Llama 3.3 70B Instruct.