Llama 3 has been superseded by Llama 4 (released April 2025). Teams using open-weight models should evaluate Llama 4 Maverick or GLM-5.
Why It's Now on Hold
Llama 3 (and 3.1) was a strong choice for self-hosted coding assistants through 2024–2025. The 70B variant offered competitive performance on a single GPU.
The open-weights landscape has moved significantly since then:
- GLM-5 (Feb 2026, already on this radar) — 744B MoE, MIT license, SWE-bench 77.8%, the current open-weights leader
- Llama 4 — Meta's next-generation family; expected to compete with GLM-5 when released
- DeepSeek V3 — Another strong open-weights option
Llama 3 weights remain freely available and the model still works, but the performance gap with newer open-weights models is substantial.
Migration Path
| If you were using Llama 3 for... | Consider |
|---|---|
| Self-hosted coding assistance | GLM-5 (if you have the compute) |
| Cost-sensitive API inference | DeepSeek V3 via API |
| Privacy / data sovereignty | GLM-5 or DeepSeek V3 (self-hosted) |
| Waiting for Meta's next release | Watch for Llama 4 |
Key Characteristics
| Property | Value |
|---|---|
| Status | Superseded |
| Successors | GLM-5, Llama 4 (upcoming) |
| Provider | Meta (open weights) |
Llama 3 is Meta's open-weight LLM family, and at the 70B parameter size it delivers competitive coding performance that can be run on your own infrastructure — without sending code to a third-party API.
Why It Matters for Engineers
Privacy and data sovereignty are real concerns when using cloud-hosted models. If your company has restrictions on sending source code to external services, self-hosted open-weight models like Llama 3 offer a practical alternative.
The 70B parameter variant in particular:
- Performs competitively with commercial models on many coding tasks
- Can run on a single high-end server GPU (e.g. an A100 or H100)
- Can be fine-tuned on your own codebase or coding style
Tradeoffs
- Requires infrastructure to run (GPU server, cloud instance, or a service like Together.ai/Groq/Fireworks)
- Smaller variants (8B) are faster but noticeably weaker for complex coding
- No built-in tool/function calling in base versions (third-party wrappers help)
How to Access It
- Download weights from Meta's website or Hugging Face
- Run via Ollama locally on a Mac or Linux machine
- Use cloud inference: Groq, Together.ai, Fireworks.ai
Key Characteristics
| Property | Value |
|---|---|
| Sizes | 8B, 70B, 405B parameters |
| Context window | 128,000 tokens (Llama 3.1+) |
| Strengths | Self-hostable, no data egress, fine-tunable |
| Provider | Meta (open weights) |