This is the AWQ version of the Llama 3.3 70B Instruct model. Find more info here: https://github.com/casper-hansen/AutoAWQ. The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks. **Model Architecture:** Llama 3.3 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.

Text generation

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llama-3-70b-instruct-awq

casperhansen

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Text generation

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llama-3-8b-instruct-awq

casperhansen

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Text generation

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mistral-7b-instruct-v0.1-awq

casperhansen

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Text generation

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mistral-nemo-instruct-2407-awq

casperhansen

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Text generation

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Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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