Phi-3-mini-4k-instruct vs Qwen3-4B-Instruct-2507
Phi-3-mini-4k-instruct (3.8B parameters) and Qwen3-4B-Instruct-2507 (4.0B parameters) side by side: the memory each needs at every precision, what it costs to run on a live GPU, and the context window, KV cache and license where they are published. Numbers are computed from the models' published specs; this page does not rank quality.
Side by side
| Fact | Phi-3-mini-4k-instruct | Qwen3-4B-Instruct-2507 |
|---|---|---|
| Parameters | 3.8B | 4.0B |
| Architecture | – | Grouped-query attention |
| Context length | 4K tokens (4,096) | 262,144 tokens |
| License | MIT | – |
| Published precision | BF16 | BF16 |
| VRAM needed, As published | 8.5 GB | 9.0 GB |
| VRAM needed, FP8 | 4.3 GB | 4.5 GB |
| VRAM needed, INT4 | 2.1 GB | 2.2 GB |
| Cheapest live fit, As published | RTX 4070 Super · $0.121/hr | RTX 4070 Super · $0.121/hr |
| Cheapest live fit, FP8 | RTX 4070 Super · $0.121/hr | RTX 4070 Super · $0.121/hr |
| Cheapest live fit, INT4 | RTX 4070 Super · $0.121/hr | RTX 4070 Super · $0.121/hr |
| KV cache per token (16-bit) | Not published for this architecture | 144 KB |
| KV cache at 32k tokens | Not published for this architecture | 4.50 GB |
| KV cache at 128k tokens | Not published for this architecture | 18.0 GB |
VRAM is the weight size at each precision times a flat 1.2 overhead; see the methodology. The FP8 and INT4 rows need a quantized checkpoint or an engine that quantizes on load. The fit is the lowest-priced single GPU type that holds the model at that precision, or the lowest-priced multi-GPU set (up to 8) when none does. KV cache is for one sequence at 16-bit, computed from each model's config where the attention layout is known.
Which to pick
- Phi-3-mini-4k-instruct needs less VRAM at its published precision (8.5 GB against 9.0 GB), so it fits on a smaller GPU.
- Qwen3-4B-Instruct-2507 lists the longer context window (262,144 tokens against 4,096).
These follow only from the facts in the table above. Whether either model does your task well is a separate question this page does not answer.
Keep reading
- Phi-3-mini-4k-instruct: full VRAM table and live GPU fit
- Qwen3-4B-Instruct-2507: full VRAM table and live GPU fit
- The Phi model series
- The Qwen model series
- All models that fit in 12 GB
Other comparisons
