Qwen 3 30B-A3B vs DeepSeek R1 Distill 32B
Side-by-side specs, benchmarks, and a verdict by use case.
Updated 2026-07-13
| Spec | Qwen 3 30B-A3B | DeepSeek R1 Distill 32B |
|---|---|---|
| Parameters | 30B | 32B |
| Author | Alibaba | DeepSeek |
| License | Apache 2.0 | MIT |
| Context window | 0k | 0k |
| VRAM at Q4 | 19 GB | 19 GB |
| VRAM at Q5 | 23 GB | 23 GB |
| VRAM at Q8 | 35 GB | 35 GB |
| VRAM at FP16 | 62 GB | 64 GB |
| Use cases | chat, general, reasoning, multilingual, moe | reasoning |
Verdict
Both models sit in a similar size class. The pick depends on tags, license, and benchmarks rather than raw parameter count.
The two models at a glance
About Qwen 3 30B-A3B
Alibaba's Qwen 3 MoE with 30B total and just 3B active parameters, supporting hybrid thinking mode. MMLU 81.4, AIME24 80.4, 100+ languages, Apache 2.0. Strengths: 3B active parameters keeps inference fast and cheap, MMLU 81.4 and AIME24 80.4 — strong on both general and reasoning, Apache 2.0, Hybrid thinking toggle per request.
About DeepSeek R1 Distill 32B
The 32B DeepSeek R1 distill — the best accessible open-weight reasoner we've tested. Explicit chain-of-thought, MIT-licensed, runs on a single 24GB GPU. Strengths: Best open-weight reasoner that fits on one consumer GPU, Excellent math and science performance, Explicit step-by-step thinking, MIT license.
How they compare
Qwen 3 30B-A3B comes from Alibaba and DeepSeek R1 Distill 32B from DeepSeek, they belong to the Qwen and DeepSeek families respectively. This comparison is built entirely from structured specs — parameter count, VRAM by quantization, context window, license, and published benchmark scores — so the verdict below reflects measurable differences rather than marketing claims.
At 30B vs 32B parameters, DeepSeek R1 Distill 32B is the larger of the two. Both need about 19 GB of VRAM at a Q4 quantization, so they fit the same GPU tier.
Where they overlap on benchmarks, Qwen 3 30B-A3B takes AIME 2024 with 80.4 against 72.6 — a clear 7.8-point margin. For workloads weighted toward that benchmark, Qwen 3 30B-A3B is the stronger default.
On a typical mid-range GPU, Qwen 3 30B-A3B pushes roughly 40 tokens/sec versus 12, so it is the more responsive choice for interactive or high-volume use. For long-context work, Qwen 3 30B-A3B offers the bigger window (128k vs 32k tokens).
Memory, quantization & throughput
Across quantization levels, Qwen 3 30B-A3B requires Q4 ≈ 19 GB, Q5 ≈ 23 GB, Q8 ≈ 35 GB, FP16 ≈ 62 GB, while DeepSeek R1 Distill 32B requires Q4 ≈ 19 GB, Q5 ≈ 23 GB, Q8 ≈ 35 GB, FP16 ≈ 64 GB. In practice Qwen 3 30B-A3B wants a 24 GB card at Q4, so plan your GPU around the Q4 or Q5 figure unless you specifically need the higher fidelity of Q8 or FP16.
Without a GPU, Qwen 3 30B-A3B needs roughly 32 GB of system RAM to run on CPU and DeepSeek R1 Distill 32B about 32 GB — workable for offline use but far slower than GPU inference. On a mid-range GPU you can expect on the order of 40 tokens/sec from Qwen 3 30B-A3B and 12 from DeepSeek R1 Distill 32B, scaling up to 100 and 30 tokens/sec on high-end hardware.
Which fits your GPU
Here is the highest-quality quantization of each model that fits common GPU memory budgets, so you can match Qwen 3 30B-A3B or DeepSeek R1 Distill 32B to the card you actually own:
- On a 24 GB GPU: Qwen 3 30B-A3B runs at Q5 (23 GB); DeepSeek R1 Distill 32B runs at Q5 (23 GB).
Benchmark scores
Reported benchmarks for Qwen 3 30B-A3B: MMLU (base) 81.38, AIME 2024 80.4.
Reported benchmarks for DeepSeek R1 Distill 32B: AIME 2024 72.6, MATH-500 94.3, GPQA 62.1.
Bottom line: which should you pick?
- Pick Qwen 3 30B-A3B for long-context work (up to 128k tokens).
- Pick Qwen 3 30B-A3B for lower VRAM and faster inference; pick DeepSeek R1 Distill 32B for maximum headline quality.
- Pick Qwen 3 30B-A3B if AIME 2024 performance is your priority (80.4 vs 72.6).
- Pick Qwen 3 30B-A3B if your workload is chat, general, moe, multilingual.
Which GPU should you buy to run Qwen 3 30B-A3B?
To run Qwen 3 30B-A3B locally at Q4, you need ~19 GB of VRAM. The best value for this is a RTX 4090 (24 GB VRAM).
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Frequently asked questions
What is the difference between Qwen 3 30B-A3B and DeepSeek R1 Distill 32B?
The headline differences: Qwen 3 30B-A3B is a 30B model and DeepSeek R1 Distill 32B is 32B; their context windows differ (128k vs 32k tokens); they ship under different licenses (Apache 2.0 vs MIT). Below we break down VRAM by quantization, benchmark scores, and a use-case verdict so you can pick the right one.
Can Qwen 3 30B-A3B and DeepSeek R1 Distill 32B run on a 24 GB GPU?
At a Q4 quantization, Qwen 3 30B-A3B needs about 19 GB of VRAM and fits comfortably on a 24 GB GPU; DeepSeek R1 Distill 32B needs about 19 GB and fits comfortably on a 24 GB GPU. Both have the same Q4 footprint.
Is Qwen 3 30B-A3B or DeepSeek R1 Distill 32B more capable?
On AIME 2024, Qwen 3 30B-A3B scores higher (80.4 vs 72.6), a 7.8-point advantage on this benchmark.
Which is faster, Qwen 3 30B-A3B or DeepSeek R1 Distill 32B?
Qwen 3 30B-A3B is the smaller model (30B vs 32B), so on the same hardware it runs faster and uses less memory. The larger model trades speed for headline quality.
What licenses do Qwen 3 30B-A3B and DeepSeek R1 Distill 32B use?
Qwen 3 30B-A3B is licensed under Apache 2.0 and DeepSeek R1 Distill 32B under MIT.
Which has the longer context window, Qwen 3 30B-A3B or DeepSeek R1 Distill 32B?
Qwen 3 30B-A3B has the larger context window (128k vs 32k tokens), so it handles longer documents and codebases in a single prompt.