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Llama 3.3 70B is now available on LlamaCoder through the Together AI API! Achieves similar performance to Llama 3.1 405B 🤯

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Hassan

92,326 subscribers

35,133 Aufrufe • vor 1 Jahr •via X (Twitter)

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7 Kommentare

Profilbild von Arturo
Arturovor 1 Jahr

@togethercompute What’s the rep for this UI builder?

Profilbild von Hassan
Hassanvor 1 Jahr

@togethercompute What do you mean?

Profilbild von AssemblyAI
AssemblyAIvor 1 Jahr

Our speech-to-text models are the most accurate on the market with top rankings across industry benchmarks. - The highest accuracy rates—up to 95% - Up to 30% fewer hallucinations than other leaders - Low latency—63 minutes converts in 35 seconds Try via API for free today 👇

Profilbild von Robert Rizk
Robert Rizkvor 1 Jahr

@togethercompute BEAST!

Profilbild von Hassan
Hassanvor 1 Jahr

@togethercompute 🙏🙏🙏

Profilbild von Gustav Ekerot
Gustav Ekerotvor 1 Jahr

@togethercompute how does it compare to something like gpt4o or claude 3.5? far behind?

Profilbild von aiokl
aioklvor 1 Jahr

@togethercompute 3 quick questions: will it ever be possible to edit published tools after publishing? How long are published tools usable? Do you have any plans to introduce Image input?

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Llama 3.3 70B 4-bit runs nicely on a 64GB M3 Max with in MLX LM (~10 toks/sec). Would be even faster on an M4 Max. Yesterday's server-only 405B is today's laptop 70B:
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Llama 3.3 70B 4-bit runs nicely on a 64GB M3 Max with in MLX LM (~10 toks/sec). Would be even faster on an M4 Max. Yesterday's server-only 405B is today's laptop 70B:

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Introducing LlamaCoder! An open source Claude Artifacts app that can generate full React apps and components with Llama 3.1 405B. 100% free and open source.
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Hassan

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Just added Qwen 2.5 32B Coder to LlamaCoder – it's an amazing open source coding model. Going to run some evals between it and Llama 3.1 405B & will share my results soon.
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Just added Qwen 2.5 32B Coder to LlamaCoder – it's an amazing open source coding model. Going to run some evals between it and Llama 3.1 405B & will share my results soon.

Hassan

52,565 Aufrufe • vor 1 Jahr

Exciting day today as Meta launches its new Llama 3.1 models and they’re available in Bedrock immediately. Llama 3.1 is a substantial step forward and the models (highlighted by the powerful 405B model) are impressive and powerful. Customers are gonna love these high performance models. Giddy up!
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Exciting day today as Meta launches its new Llama 3.1 models and they’re available in Bedrock immediately. Llama 3.1 is a substantial step forward and the models (highlighted by the powerful 405B model) are impressive and powerful. Customers are gonna love these high performance models. Giddy up!

Andy Jassy

45,000 Aufrufe • vor 1 Jahr

🤯🤯 You can now create a chatbot on ANY GitHub repo using the Llama 3.1 405B model with Hugging Face assistants -- FOR FREE! 💰 This is insane! 🚀 Link: clem 🤗 Julien Chaumond
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🤯🤯 You can now create a chatbot on ANY GitHub repo using the Llama 3.1 405B model with Hugging Face assistants -- FOR FREE! 💰 This is insane! 🚀 Link: clem 🤗 Julien Chaumond

Satvik Paramkusham

162,848 Aufrufe • vor 1 Jahr

2 MacBooks is all you need. Llama 3.1 405B running distributed across 2 MacBooks using exo intern home AI cluster
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2 MacBooks is all you need. Llama 3.1 405B running distributed across 2 MacBooks using exo intern home AI cluster

Alex Cheema

1,287,756 Aufrufe • vor 1 Jahr

2024 AI timeline - it has been a truly WILD year! 🔥 From Gemma to Llama 3.1 405B to Sonnet 3.5 to o3 AND MORE! Put together a non-exhaustive list of Open and API releases from the year - looking forward to 2025 🤗
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2024 AI timeline - it has been a truly WILD year! 🔥 From Gemma to Llama 3.1 405B to Sonnet 3.5 to o3 AND MORE! Put together a non-exhaustive list of Open and API releases from the year - looking forward to 2025 🤗

Vaibhav (VB) Srivastav

80,574 Aufrufe • vor 1 Jahr

With the release of Llama 3.1 405B, @TogetherCompute built LlamaCoder — an open source web app that can generate an entire app from a prompt. The repo has now been cloned by hundreds of devs on GitHub and starred 2K+ times. More on this project ➡️
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With the release of Llama 3.1 405B, @TogetherCompute built LlamaCoder — an open source web app that can generate an entire app from a prompt. The repo has now been cloned by hundreds of devs on GitHub and starred 2K+ times. More on this project ➡️

AI at Meta

260,520 Aufrufe • vor 1 Jahr

This is the fastest I've seen Llama 3.3 running anywhere! Llama 3.3 70B running at 652 t/s is lightning fast. And if you want Llama 3.1, here are the speeds I was able to get: • Llama 3.1 8B: 1006 t/s • Llama 3.1 70B: 709 t/s • Llama 3.1 405B: 206 t/s (You can access all of these models for free! See the link below.) This speed is incredible, but the interesting part is what's happening behind the scenes: These models aren't running on a GPU! In this video, I'm using the SambaNova cloud to access these models. They built a custom chip (SN40L) optimized for AI workflows. A single SN40L chip can hold hundreds of models (trillions of parameters) in memory! The speed alone is a huge deal, but the big advantage is for agentic workflows running multiple specialized models. A GPU can only host a single model and switch (unload and load) to a different model if necessary. An SN40L, on the other hand, can host every model at once, making it much faster. Here is the video where you can see how fast these chips are:
7:24

This is the fastest I've seen Llama 3.3 running anywhere! Llama 3.3 70B running at 652 t/s is lightning fast. And if you want Llama 3.1, here are the speeds I was able to get: • Llama 3.1 8B: 1006 t/s • Llama 3.1 70B: 709 t/s • Llama 3.1 405B: 206 t/s (You can access all of these models for free! See the link below.) This speed is incredible, but the interesting part is what's happening behind the scenes: These models aren't running on a GPU! In this video, I'm using the SambaNova cloud to access these models. They built a custom chip (SN40L) optimized for AI workflows. A single SN40L chip can hold hundreds of models (trillions of parameters) in memory! The speed alone is a huge deal, but the big advantage is for agentic workflows running multiple specialized models. A GPU can only host a single model and switch (unload and load) to a different model if necessary. An SN40L, on the other hand, can host every model at once, making it much faster. Here is the video where you can see how fast these chips are:

Santiago

97,505 Aufrufe • vor 1 Jahr

Introducing `llama-405b-to-8b` ✍️ Get the quality of Llama 3.1 405B, at a fraction of the cost and latency. Give one example of your task, and 405B will teach 8B (~30x cheaper!!) how to do the task perfectly. And it's open-source:
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Introducing `llama-405b-to-8b` ✍️ Get the quality of Llama 3.1 405B, at a fraction of the cost and latency. Give one example of your task, and 405B will teach 8B (~30x cheaper!!) how to do the task perfectly. And it's open-source:

Matt Shumer

278,384 Aufrufe • vor 1 Jahr

DeepSeek R1 671B is ridiculously good, but running at 158 tokens per second is something out of this world. A model *this good* running *this fast* is 3 years ahead of this time. The secret: DeepSeek in this short video isn't running on GPUs. It's running on custom-made chips! This is running on SambaNova and their SN40L chips, which are designed and optimized for running AI workflows. SambaNova is sponsoring my work. We designed GPUs to run games and later realized we could use them for AI. This is very different from creating a chip specifically for AI from the ground up. Just think about this for a second: One single SNL40 chip can simultaneously hold 100+ models (trillions of parameters) in memory! An agentic workflow that uses multiple models simultaneously won't need to swap models from memory even once! By the way, the Llama family of models *screams* on the SambaNova Cloud. Here are some numbers from my latest tests: • Llama 3.3 70B: 367.32 t/s • Llama 3.2 1B: 2381.82 t/s • Llama 3.2 3B: 1335.71 t/s • Llama 3.1 8B: 929.58 t/s • Llama 3.1 70B: 369.16 t/s • Llama 3.1 405B: 103.37 t/s You can access all of these models for free!
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DeepSeek R1 671B is ridiculously good, but running at 158 tokens per second is something out of this world. A model *this good* running *this fast* is 3 years ahead of this time. The secret: DeepSeek in this short video isn't running on GPUs. It's running on custom-made chips! This is running on SambaNova and their SN40L chips, which are designed and optimized for running AI workflows. SambaNova is sponsoring my work. We designed GPUs to run games and later realized we could use them for AI. This is very different from creating a chip specifically for AI from the ground up. Just think about this for a second: One single SNL40 chip can simultaneously hold 100+ models (trillions of parameters) in memory! An agentic workflow that uses multiple models simultaneously won't need to swap models from memory even once! By the way, the Llama family of models *screams* on the SambaNova Cloud. Here are some numbers from my latest tests: • Llama 3.3 70B: 367.32 t/s • Llama 3.2 1B: 2381.82 t/s • Llama 3.2 3B: 1335.71 t/s • Llama 3.1 8B: 929.58 t/s • Llama 3.1 70B: 369.16 t/s • Llama 3.1 405B: 103.37 t/s You can access all of these models for free!

Santiago

130,934 Aufrufe • vor 1 Jahr

With today’s launch of our Llama 3.1 collection of models we’re making history with the largest and most capable open source AI model ever released. 128K context length, multilingual support, and new safety tools. Download 405B and our improved 8B & 70B here.
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With today’s launch of our Llama 3.1 collection of models we’re making history with the largest and most capable open source AI model ever released. 128K context length, multilingual support, and new safety tools. Download 405B and our improved 8B & 70B here.

Ahmad Al-Dahle

866,426 Aufrufe • vor 1 Jahr

My open source Claude Artifacts app using Llama 3.1 405B is dropping in 24 hours! Free & fully open source.
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My open source Claude Artifacts app using Llama 3.1 405B is dropping in 24 hours! Free & fully open source.

Hassan

272,373 Aufrufe • vor 1 Jahr

Instant Intelligence is wild with Llama 3.1 8B + Groq 🤯
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Instant Intelligence is wild with Llama 3.1 8B + Groq 🤯

Min Choi

692,933 Aufrufe • vor 1 Jahr

Our Llama-3.1-Nemotron-70B-Instruct model is a leading model on the 🏆 Arena Hard benchmark (85) from Arena. Arena Hard uses a data pipeline to build high-quality benchmarks from live data in Chatbot Arena, and is known for its predictive ability of Chatbot Arena Elo score as well as separability between helpful and less helpful models. Use our customized model Llama-3.1-Nemotron-70B to improve the helpfulness of LLM generated responses in your applications. 📥 Try on our API catalog: 📥 On GitHub: 📥 Or on Hugging Face:
0:43

Our Llama-3.1-Nemotron-70B-Instruct model is a leading model on the 🏆 Arena Hard benchmark (85) from Arena. Arena Hard uses a data pipeline to build high-quality benchmarks from live data in Chatbot Arena, and is known for its predictive ability of Chatbot Arena Elo score as well as separability between helpful and less helpful models. Use our customized model Llama-3.1-Nemotron-70B to improve the helpfulness of LLM generated responses in your applications. 📥 Try on our API catalog: 📥 On GitHub: 📥 Or on Hugging Face:

NVIDIA AI Developer

140,756 Aufrufe • vor 1 Jahr

deepseek-r1-distill-llama-70b on groq
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deepseek-r1-distill-llama-70b on groq

Developers Digest

143,277 Aufrufe • vor 1 Jahr