Model → hardware
Qwen2.5-Coder 7B
Plan for 6 GB of dedicated GPU memory at Q4_K_M and a 4,000-token context. 12 GB gives more headroom under the same settings.
Coding with a smaller memory budget. Memory fit is an estimate, not a speed or quality guarantee.
Hardware starting points
Planning estimatesQ4_K_M · 32 GB system RAM · one active request · full GPU residency
| Dedicated GPU memory | At 4,000 tokens | At 16,000 tokens | Example from these guides |
|---|---|---|---|
| 6 GB | Smallest listed tier that fits5.8 GB + 0.18 GB reserve | Exceeds this budget6.5 GB + reserve | RTX 2060 6 GB |
| 8 GB | Fits, with limited headroom5.8 GB + 0.24 GB reserve | Fits the estimate6.5 GB + reserve | RTX 4060 8 GB |
| 12 GB | More headroom5.8 GB + 0.36 GB reserve | Fits the estimate6.5 GB + reserve | RTX 3060 12 GB |
The smallest tier fits the calculation; it is not a verified minimum. Cache precision and runtime buffers can change the fit. “More headroom” means at least 2 GB remains after the estimate and reserve.
Use the publisher’s Instruct / chat template in a current GGUF-capable runtime. The 6 GB tier can become tight when display use, buffers or context grow. CPU offloading needs adequate system RAM and changes performance; it is not included in these full-GPU estimates.
Compare quantisation and context
| File profile | Weight input¹ | GPU estimate at 4K | GPU estimate at 16K |
|---|---|---|---|
| Q4_K_M | 4.68 GB | 5.8 GB | 6.5 GB |
| Q5_K_M | 5.44 GB | 6.6 GB | 7.2 GB |
¹ Catalogue planning weights. These can differ from an exact downloaded file; runtime memory also includes cache and buffers.
Keep the exact file, runtime version, cache type and context limit consistent when comparing. Q5 uses more memory; compare its answers on your own tasks before accepting the trade-off.
Setup and common questions
Which files do I need?
Choose Qwen/Qwen2.5-Coder-7B-Instruct for conversational coding. The official GGUF directory includes merged files and split versions. Use one complete version: either the merged file or all numbered shards of the selected quant.
How should I check its output?
Start with one function, a clear expected result and tests you can run. Use the Instruct chat template. Compare Q4 and Q5 on the same task; review generated code and dependencies.
Can I use the advertised 128K context?
The standard configuration starts at 32,768 tokens; longer context requires YaRN and runtime support. The GGUF card has further limits. Confirm support in your exact app and budget for the cache.
How are these recommendations chosen?
We compare dedicated GPU memory tiers using the main Finder’s memory calculation at the stated quantisation and context. These tiers describe memory fit, not speed or output quality.
GPU memory includes weights, context cache and a 0.9 GB runtime allowance, plus a 3% reserve (0.15–1.5 GB). Cache format and runtime buffers can change the fit. See the calculation assumptions.
Sources and related guides
Specification sources checked 2 October 2026.
These comparisons are planning estimates. No reviewed or independently reproduced measurements are available yet. About test evidence.