Both are excellent open coding models that run on a single card. But they're tuned differently, and the right one depends on how you code. Here's the honest comparison.
If you want a coding model running locally on a single GPU in 2026, two names lead the field: Qwen3-Coder-30B-A3B and DeepSeek's coding models. Both are excellent, both are open, and both fit a 24GB card — so the choice isn't about which is 'better' in the abstract, but which suits how you actually code. Qwen3-Coder's Mixture-of-Experts design makes it fast and strong on multi-file work; DeepSeek's lineage brings careful, reasoning-heavy code. Here's the honest comparison to pick the right one for your GPU.
How they differ in practice
The practical difference comes down to speed versus reasoning style. Qwen3-Coder-30B-A3B is a Mixture-of-Experts model — 30B total but only ~3B active per token — so it generates fast, which makes it feel great as an interactive assistant for completions, refactors and multi-file edits. DeepSeek's coding models lean into careful, step-by-step reasoning, which can produce more thought-through code on harder problems at the cost of some speed. Neither is universally better: if you want snappy, in-the-flow help, Qwen3-Coder; if you want a model that thinks harder about a gnarly problem, DeepSeek. For most interactive coding, the MoE speed of Qwen3-Coder is the more pleasant daily driver.
Qwen3-Coder vs DeepSeek-Coder
Qwen3-Coder-30B
MoE · fast
vs
DeepSeek-Coder
Reasoning-heavy
Fast (MoE)
Speed
Slower
Strong
Multi-file
Strong
Good
Reasoning depth
Excellent
Snappy
Interactive feel
More deliberate
Yes
Fits 24GB
Yes
Qwen3-Coder-30B wins 2wins 1 DeepSeek-Coder
Both models run on one 24GB card. The choice is about coding style — snappy MoE (Qwen) vs deliberate reasoning (DeepSeek). · Unsplash
Which to run
My honest recommendation: start with Qwen3-Coder-30B-A3B as your daily driver — its speed makes it the more pleasant interactive coding companion, and it's genuinely strong on multi-file work. Keep a DeepSeek coding model around for when you hit a hard problem that benefits from more deliberate reasoning. Since both are free and both fit a 24GB card, there's no reason not to have both installed and switch based on the task. For the full local-coding setup including hardware, see our best local coding model guide.
Quick answers
Is Qwen3-Coder or DeepSeek-Coder better for local coding?
Neither is universally better — they suit different styles. Qwen3-Coder-30B-A3B is faster (thanks to its MoE design) and excellent for interactive, multi-file coding, making it the better daily driver for most people. DeepSeek's coding models reason more deliberately, which helps on harder, more novel problems at some cost to speed. Try both (they're free and both fit a 24GB card) and keep whichever matches your workflow, or switch between them by task.
What GPU do I need to run these coding models?
A single 24GB card handles both comfortably — a used RTX 3090 (~$1,000) is the value host, and a 4090 runs them faster. The 30B-class coding models need about 20GB at Q4, so 24GB is the target. On a 16GB card you'd drop to a 14B coding model, which is still useful but a step down in multi-file coherence. For the best local coding experience, 24GB is the tier to aim for.
Can I run these coding models for free?
Yes — both Qwen3-Coder and DeepSeek's coding models are open-weight and free to download and run locally. Your only costs are the hardware (a 24GB GPU) and electricity. That's the appeal of local coding models: no per-token API bills, no rate limits, and your code never leaves your machine. Once you own a capable card, running these models costs nothing per use, which adds up fast versus paid coding APIs.
Run Qwen3-Coder-30B-A3B as your fast daily coding driver, keep a DeepSeek model for deep-reasoning tasks, and switch by need — both are free and fit a 24GB card. See the full local coding guide for the complete setup.
