GPT-6 Sol vs Llama 3.2 90B Instruct
GPT-6 Sol leads the LLM Stats Score 49.4 to 5.2. Llama 3.2 90B Instruct is 11.0x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-6 Sol leads the overall LLM Stats Score 49.4 to 5.2, ranking #21 overall.
On price, Llama 3.2 90B Instruct is roughly 11.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Sol also accepts a larger context window (1,050,000 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 GPT-6 Sol
- overall performance matters — it scores 49.4 and ranks #21 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Llama 3.2 90B Instruct
- cost matters — it's about 11.0x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
5 reported for GPT-6 Sol · 13 for Llama 3.2 90B Instruct
GPT-6 Sol and Llama 3.2 90B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Sol ($2.00/1M tokens) is 5.7x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, GPT-6 Sol ($10.00/1M tokens) is 25.0x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, GPT-6 Sol is more expensive than Llama 3.2 90B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Sol accepts 1,050,000 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-6 Sol and Llama 3.2 90B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6 Sol
Llama 3.2 90B Instruct
License
Usage and distribution terms
GPT-6 Sol is licensed under a proprietary license, while Llama 3.2 90B Instruct uses Llama 3.2.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.2
Open weights
Release Timeline
When each model was launched
GPT-6 Sol was released on 2026-09-22, while Llama 3.2 90B Instruct was released on 2024-09-25.
GPT-6 Sol is 24 months newer than Llama 3.2 90B Instruct.
Sep 22, 2026
0 days ago
2.0yr newerSep 25, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
GPT-6 Sol has a documented knowledge cutoff of 2026-04-20, while Llama 3.2 90B Instruct's cutoff date is not specified.
We can confirm GPT-6 Sol's training data extends to 2026-04-20, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.
Apr 2026
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Provider Availability
GPT-6 Sol is available from OpenAI. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.
GPT-6 Sol
Llama 3.2 90B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Sol and Llama 3.2 90B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Sol vs Llama 3.2 90B Instruct.