Code Llama, which is built on top of Llama 2, is free for research and commercial use.
I don't see any actual user reviews or social mentions about CodeLlama in your message. The only content provided appears to be an incomplete GitHub commit message about Vertex AI pricing updates, which doesn't contain user feedback about CodeLlama specifically. To provide an accurate summary of user sentiment about CodeLlama, I would need actual user reviews, GitHub issues, social media posts, or other user-generated content that discusses their experiences with the tool. Could you please share the relevant user feedback you'd like me to analyze?
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I don't see any actual user reviews or social mentions about CodeLlama in your message. The only content provided appears to be an incomplete GitHub commit message about Vertex AI pricing updates, which doesn't contain user feedback about CodeLlama specifically. To provide an accurate summary of user sentiment about CodeLlama, I would need actual user reviews, GitHub issues, social media posts, or other user-generated content that discusses their experiences with the tool. Could you please share the relevant user feedback you'd like me to analyze?
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HuggingFace models
Meta Ray-Ban Display + Meta Neural Band = our most advanced pair of AI glasses. Ever. https://t.co/PlrVcwbprN
Meta Ray-Ban Display + Meta Neural Band = our most advanced pair of AI glasses. Ever. https://t.co/PlrVcwbprN
View originalchore(pricing): Update vertex-ai pricing
## 🔄 Pricing Update: vertex-ai ### 📊 Summary (complete_diff mode) | Change Type | Count | |-------------|-------| | ➕ Models added | 70 | | 🔄 Models updated (merged) | 24 | ### ➕ New Models - `gemini-2.5-computer-use-preview-10-2025` - `gemini-2.5-flash-preview-09-2025` - `gemini-2.5-flash-lite-preview-09-2025` - `gemini-3.1-flash-lite-preview` - `imagen-3.0-generate-002` - `imagen-3.0-capability-002` - `imagen-product-recontext-preview-06-30` - `text-embedding-large-exp-03-07` - `multimodalembedding` - `gpt-oss` - `gpt-oss-120b-maas` - `whisper-large` - `mistral` - `mixtral` - `mistral-small-2503` - `codestral-2501-self-deploy` - `mistral-ocr-2505` - `mistral-medium-3` - `codestral-2` - `ministral-3` - ... and 50 more ### 🔄 Updated Models - `gemini-2.5-pro` - `gemini-2.5-flash` - `gemini-2.5-flash-lite` - `gemini-2.5-flash-image` - `gemini-2.5-flash-image-preview` - `gemini-3.1-pro-preview` - `gemini-3-pro-preview` - `gemini-3-pro-image-preview` - `imagen-4.0-generate-001` - `imagen-4.0-fast-generate-001` - `imagen-4.0-ultra-generate-001` - `imagen-4.0-generate-preview-06-06` - `imagen-4.0-fast-generate-preview-06-06` - `imagen-4.0-ultra-generate-preview-06-06` - `imagen-3.0-capability-001` - `veo-3.0-generate-001` - `veo-3.0-fast-generate-001` - `veo-3.0-generate-preview` - `veo-3.0-fast-generate-preview` - `veo-3.1-generate-001` - `veo-3.1-generate-preview` - `veo-3.1-fast-generate-preview` - `text-embedding-005` - `text-multilingual-embedding-002` ## Model-to-Pricing-Page Mapping | Model ID | Publisher / Section | Source | Notes | |----------|-------------------|--------|-------| | `gemini-2.5-pro` | Google – Gemini 2.5 | API | $1.25/$10 input/output (≤200K); cache read $0.125 | | `gemini-2.5-flash` | Google – Gemini 2.5 | API | $0.30/$2.50; cache $0.03; image_token $30/1M | | `gemini-2.5-flash-lite` | Google – Gemini 2.5 | API | $0.10/$0.40; cache $0.01 | | `gemini-2.5-flash-image` | Google – Gemini 2.5 | API | Same as gemini-2.5-flash with image output | | `gemini-2.5-flash-image-preview` | Google – Gemini 2.5 | API | Same as gemini-2.5-flash (preview alias) | | `gemini-2.5-computer-use-preview-10-2025` | Google – Gemini 2.5 | API | Matched as "Gemini 2.5 Pro Computer Use-Preview"; $1.25/$10, no cache | | `gemini-2.5-flash-preview-09-2025` | Google – Gemini 2.5 | API | Preview alias of gemini-2.5-flash; same pricing | | `gemini-2.5-flash-lite-preview-09-2025` | Google – Gemini 2.5 | API | Preview alias of gemini-2.5-flash-lite; same pricing | | `gemini-2.0-flash-001` | Google – Gemini 2.0 | API | $0.15/$0.60; batch $0.075/$0.30 | | `gemini-2.0-flash-lite-001` | Google – Gemini 2.0 | API | $0.075/$0.30; batch $0.0375/$0.15 | | `gemini-3.1-pro-preview` | Google – Gemini 3 | API | $2/$12; cache $0.2; web_search 1.4¢ | | `gemini-3-pro-preview` | Google – Gemini 3 | API | $2/$12; cache $0.2; web_search 1.4¢ | | `gemini-3-pro-image-preview` | Google – Gemini 3 | API | $2/$12; image_token $120/1M; web_search 1.4¢ | | `gemini-3.1-flash-image-preview` | Google – Gemini 3 | API | $0.50/$3; image_token $60/1M; web_search 1.4¢ | | `gemini-3.1-flash-lite-preview` | Google – Gemini 3 | API | $0.25/$1.50; cache $0.025; web_search 1.4¢ | | `gemini-3-flash-preview` | Google – Gemini 3 | API | $0.50/$3; cache $0.05; web_search 1.4¢ | | `imagen-4.0-generate-001` | Google – Imagen | API | Row matched via lookup_variant `imagen-4.0-generate`; $0.04/image | | `imagen-4.0-fast-generate-001` | Google – Imagen | API | Row matched via `imagen-4.0-fast-generate`; $0.02/image | | `imagen-4.0-ultra-generate-001` | Google – Imagen | API | Row matched via `imagen-4.0-ultra-generate`; $0.06/image | | `imagen-4.0-generate-preview-06-06` | Google – Imagen | API | Preview; matched as Imagen 4; $0.04/image | | `imagen-4.0-fast-generate-preview-06-06` | Google – Imagen | API | Preview; matched as Imagen 4 Fast; $0.02/image | | `imagen-4.0-ultra-generate-preview-06-06` | Google – Imagen | API | Preview; matched as Imagen 4 Ultra; $0.06/image | | `imagen-3.0-generate-002` | Google – Imagen | API | Row matched via `imagen-3.0-generate`; $0.04/image | | `imagen-3.0-capability-001` | Google – Imagen | API – price not found | Editing/VQA feature model; no pricing row | | `imagen-3.0-capability-002` | Google – Imagen | API – price not found | Editing/VQA feature model; no pricing row | | `imagen-product-recontext-preview-06-30` | Google – Imagen | API | "Imagen Product Recontext"; $0.12/image | | `veo-2.0-generate-001` | Google – Veo | API | Row matched via `veo-2.0-generate`; $0.50/sec | | `veo-3.0-generate-001` | Google – Veo | API | Row matched as Veo 3 (video+audio rate); $0.40/sec | | `veo-3.0-fast-generate-001` | Google – Veo | API | Row matched as Veo 3 Fast; $0.15/sec | | `veo-3.0-generate-preview` | Google – Veo | API | Preview alias of Veo 3; $0.40/sec | | `veo-3.0-fast-generate-preview` | Google – Veo | API | Preview alias of Veo 3 Fast; $0.15/sec | | `veo-3.1-generate-001` | Google – Veo | API | Row matched as Veo 3.1; $0
View originalWith the help of DINO, our open source computer vision model, the UK's Forest Research agency is growing something beautiful 🌳 https://t.co/UdkemeKGUj
With the help of DINO, our open source computer vision model, the UK's Forest Research agency is growing something beautiful 🌳 https://t.co/UdkemeKGUj
View original@BreezeAmal in the moments when it matters most
@BreezeAmal in the moments when it matters most
View originalDid you know we're working with environmental survey teams to improve flood detection? Our Segment Anything Model (SAM) is being used to identify minute changes in water conditions from satellite imag
Did you know we're working with environmental survey teams to improve flood detection? Our Segment Anything Model (SAM) is being used to identify minute changes in water conditions from satellite images—we hope this faster analysis can contribute to better rapid response and keep communities safer.
View originalWe’re partnering with @AMD to integrate their GPUs into our infrastructure—that means more compute power to bring our AI experiences to even more people. https://t.co/XHCSOi5uTy
We’re partnering with @AMD to integrate their GPUs into our infrastructure—that means more compute power to bring our AI experiences to even more people. https://t.co/XHCSOi5uTy
View originalAthletic Intelligence is here. Push your training to the edge with Oakley Meta Performance AI glasses. Hands-free camera. Meta AI. Open-ear audio. Consider the game changed. https://t.co/DXGxKlAmPF
Athletic Intelligence is here. Push your training to the edge with Oakley Meta Performance AI glasses. Hands-free camera. Meta AI. Open-ear audio. Consider the game changed. https://t.co/DXGxKlAmPF
View originalMeta Ray-Ban Display + Meta Neural Band = our most advanced pair of AI glasses. Ever. https://t.co/PlrVcwbprN
Meta Ray-Ban Display + Meta Neural Band = our most advanced pair of AI glasses. Ever. https://t.co/PlrVcwbprN
View originalWe go together like AI and glasses—is that not an expression? It will be. Check out all the news from Connect 2025. https://t.co/PQfVQROS3u
We go together like AI and glasses—is that not an expression? It will be. Check out all the news from Connect 2025. https://t.co/PQfVQROS3u
View original@Dilmerv you and us both 🤝
@Dilmerv you and us both 🤝
View original@codemiko us patiently waiting: 🧘
@codemiko us patiently waiting: 🧘
View original@BenBajarin the vibes we bring to the function
@BenBajarin the vibes we bring to the function
View original@GameDevMicah gonna be singing this the rest of the day
@GameDevMicah gonna be singing this the rest of the day
View original@JonathanWinbush feeling is mutual
@JonathanWinbush feeling is mutual
View originalRepository Audit Available
Deep analysis of meta-llama/codellama — architecture, costs, security, dependencies & more
CodeLlama uses a tiered pricing model. Visit their website for current pricing details.
Key features include: We are releasing Code Llama 70B, the largest and best-performing model in the Code Llama family, CodeLlama - 70B, the foundational code model;, CodeLlama - 70B - Python, 70B specialized for Python;, and Code Llama - 70B - Instruct 70B, which is fine-tuned for understanding natural language instructions., Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts., Code Llama is free for research and commercial use., Code Llama, the foundational code model;, Codel Llama - Python specialized for Python;.
CodeLlama has a public GitHub repository with 16,334 stars.
Based on user reviews and social mentions, the most common pain points are: token cost.
Based on 23 social mentions analyzed, 0% of sentiment is positive, 100% neutral, and 0% negative.
