Meta releases Code Llama 70B, a new version of its code generation model, featuring improved code correctness, a variant optimized for Python, and more
available under the same license as previous Code Llama models. Download the models ➡️ https://ai.meta.com/... • CodeLlama-70B • CodeLlama-70B-Python • CodeLlama-70B-Instruct [image] Awni Hannun / @awnihannun : 4-bit quantized Code Llama models already in the 🤗 MLX Community! {70, 13, 7}B models here: https://huggingface.co/... 1. pip install mlx-lm 2. python -m mlx_lm.generate —model mlx-community/CodeLlama-13b-Python- 4bit —prompt “write a quick sort in C++” Thanks to... Robert Scoble / @scobleizer : Apple AI: 4-bit quantized means they run fast on phones and other small computers. And three different models. Big to do college essays. Small to answer you fast. Medium to find you a restaurant to eat dinner at. New Siri! Robert Scoble / @scobleizer : The AI models are raining out of the sky. Happy Monday! Josh Wolfe / @wolfejosh : Open source is the way. @huggingface + @Meta Gabriel Synnaeve / @syhw : I was logging after a long day just to say that: Baptiste Rozière / @b_roziere : We released a 70B version of CodeLlama today! Trained on 1T tokens, it is a much stronger base model for coding tasks. I look forward to seeing what the community will do with it! :) Yann LeCun / @ylecun : The new breed of CodeLlamas comes with source, like their predecessor. Joelle Pineau / @jpineau1 : We just shared a new larger and improved Code Llama 70B parameter model. With every release, we have better generation quality, but also a better sense of how to make these models safe. @ollama : @DrTBehrens We just updated the model template to make it better. (No need to redownload the whole thing... it'll automatically download the diff which is very small). Just run: ollama pull codellama:70b Sorry for the hassle! Elvis / @omarsar0 : Code Llama 70B is here! It achieves 67.8 on HumanEval. Meta AI is releasing the following models: • CodeLlama-70B • CodeLlama-70B-Python • CodeLlama-70B-Instruct It's going to be interesting to see how these models are used and potentially fine-tuned to create even more... @ollama : .@AIatMeta's codellama 70B is here! It achieves 67.8% on HumanEval which reaches the initial GPT-4 performance 🤯🤯 To run it: ollama run codellama:70b Learn more: https://ollama.ai/... [image] Philipp Schmid / @_philschmid : Code Llama 70B is here!🤯🧑🏻💻 @AIatMeta just released CodeLlama 70B, the latest and biggest iteration of Code Llama! 🚀 Code Llama 70B achieves 67.8% on HumanEval, reaching the initial GPT-4 performance! 👨🏫 Key facts✨: 🧮 70B parameter initialized from Llama 2 🔠 Trained on 500B... [image] Soumith Chintala / @soumithchintala : new CodeLlama 70B drop from @syhw and team. Offline benchmarks look pretty good, but try it out and see for yourself! [image] @reach_vb : CodeLlama 70B -> Beats GPT 4, Palm-Coder to punch! 👊 Open weights ftw!! [image] Harrison Kinsley / @sentdex : I have found tunes of Code Llama 34B to be close enough to what GPT-4 did for me to cancel my sub to GPT-4. With Code Llama 70B finally released, the subsequent tunes can further seal the fate of closed AI for coding models where OSS AI is just plain better in every way. From... @_akhaliq : Meta releases Code Llama 70B models: https://huggingface.co/... CodeLlama-70B-Instruct achieves 67.8 on HumanEval, making it one of the highest performing open models available [image] Omar Sanseviero / @osanseviero : Code Llama 70B is here! 🚀🦙🤖 Find the models in transformers format - Base https://hf.co/... - Python https://hf.co/... - Instruct https://hf.co/... Enjoy and code! Note: the instruct model has a different template than the smaller instruct models [image] LinkedIn: Ahmad Al-Dahle : Code Llama 70B update! — In August of last year, we released Code Llama, Code Llama - Instruct, and Code Llama - Python, all in 3 sizes: 7B, 13B, and 34B parameters. … Facebook: Mark Zuckerberg : We're open sourcing a new and improved Code Llama, including a larger 70B parameter model. … Forums: Hacker News : Meta AI releases Code Llama 70B r/singularity : Today we're releasing Code Llama 70B: a new, more performant version of our LLM for code generation — available under the same license as previous Code Llama models.
Context & Ripple Effects
Meta had already positioned Code Llama as a code-generation and debugging model under a community license that permitted research and commercial use. This 70B release extends that initial Code Llama rollout with a larger family, a Python-focused option and an instruction-tuned variant.
The release matters because it makes a higher-capability coding model available through the same distribution approach rather than reserving it for a hosted product. It also establishes a base that Meta later used for LLM Compiler models focused on code optimization.
First-order effects
- Developers and organizations can download and run three 70B Code Llama variants, selecting general-purpose, Python-oriented or instruction-following behavior for coding workflows.
- Meta strengthens its coding-model offering with reported correctness gains; CodeLlama-70B-Instruct’s 67.8% HumanEval result gives users a public benchmark for evaluating it against prior options.
Second-order effects
- Open availability gives developer-tool builders and infrastructure providers another model family to package, fine-tune, quantize and deploy, shifting differentiation toward integration, tooling and runtime efficiency.
- Competing code-model providers face greater pressure to show measurable quality gains or offer easier deployment, particularly for users seeking Python-specific generation without relying on a single hosted service.
Third-order effects
- If capable code models continue to be released as downloadable weights, value in the coding-AI market is likely to concentrate less in raw model access and more in proprietary data, workflow integration, evaluation and operational support.
- The release also points to a more segmented model stack: broad foundation models can be adapted into specialized coding and optimization systems, though benchmark performance alone will not determine production adoption.
The trend: This is part of the open-weight complement economy, where accessible foundation models create competition around specialized variants, deployment and developer-facing products.