Smaller alternatives
Models that need less memory than Olmo 3 7B and score about as well or better.
Olmo 3 7B Instruct
Allen Institute for AI · 7.3B · Dense
Olmo 3 7B Instruct is a 7.3B model from Allen Institute for AI with a 64K-token context. At Q4_K_M with an 8K context it needs about 7 GB; 10 GB leaves room for longer chats.
Quantization options
| Quant | Bits | Memory | Quality | On your hardware |
|---|---|---|---|---|
| Q2_K | 3.16 | — | Noticeably worse | … |
| Q3_K_M | 4 | — | Some loss | … |
| Q4_K_M | 4.89 | — | Good | … |
| Q5_K_M | 5.7 | — | Good | … |
| Q6_K | 6.56 | — | Near original | … |
| Q8_0 | 8.5 | — | Near original | … |
| F16 | 16 | — | Original | … |
Memory by context length
At Q4_K_M. The context cache grows with every token the model keeps in mind.
| Context | Context cache | Total |
|---|---|---|
| 4K | 2 GB | 6.5 GB |
| 8K | 2.5 GB | 7 GB |
| 32K | 5.5 GB | 10 GB |
Next steps
Compare it with
Scored models of a similar size, side by side on your device.
Least hardware that runs it well
Desktop devices with the least memory that give Olmo 3 7B grade A or S at Q4_K_M.
Can I run Olmo 3 7B Instruct locally?
Can I run Olmo 3 7B Instruct locally?
Yes, if your GPU or Mac has about 7 GB free for it at Q4_K_M. Open this page on that computer to see the grade for your exact hardware, then start it with llama.cpp, Ollama or LM Studio.
How much memory does Olmo 3 7B Instruct need?
About 7 GB at Q4_K_M with an 8K context and 10 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.