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DeepSeek R1 Distill Llama 70B vs DeepSeek R1 Distill Qwen 32B

Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.

Quick verdict

DeepSeek R1 Distill Qwen 32B is more hardware-efficient — it needs 20.6 GB at Q4_K_M vs 42.2 GB for DeepSeek R1 Distill Llama 70B, fitting on 51 GPUs natively.

VRAM at each quantization (8k context)

QuantDeepSeek R1 Distill Llama 70BDeepSeek R1 Distill Qwen 32BDiff
FP16159.8 GB75.2 GB+112%
Q881.4 GB38.8 GB+110%
Q6_K61.8 GB29.7 GB+108%
Q5_K_M52.0 GB25.2 GB+107%
Q4_K_M42.2 GB20.6 GB+105%
Q3_K_M34.4 GB17.0 GB+103%
Q2_K26.5 GB13.3 GB+99%

Diff is DeepSeek R1 Distill Llama 70B relative to DeepSeek R1 Distill Qwen 32B. Green = lower VRAM (fits more GPUs).

Model specifications

SpecDeepSeek R1 Distill Llama 70BDeepSeek R1 Distill Qwen 32B
OrgDeepSeekDeepSeek
Parameters70B32.5B
ArchitectureDenseDense
Context125k tokens125k tokens
Modalitiestexttext
LicenseMITMIT
CommercialYesYes
Released2025-01-202025-01-20
GPUs (native)38 / 6751 / 67

Benchmark scores

BenchmarkDeepSeek R1 Distill Llama 70BDeepSeek R1 Distill Qwen 32B
MMLU-Pro70.065.0
GPQA65.262.1
MATH94.594.3
HumanEval88.887.2

Green = higher score (better). — = not yet available.

GPUs that run only DeepSeek R1 Distill Llama 70B(0)

Every GPU that runs DeepSeek R1 Distill Llama 70B also runs DeepSeek R1 Distill Qwen 32B.

GPUs that run only DeepSeek R1 Distill Qwen 32B(13)

GPUs that run both natively(38)

Which should you use?

Choose DeepSeek R1 Distill Llama 70B if:
  • • You want maximum capability and have a 43 GB+ GPU
  • • Benchmark quality matters — scores 70.0 vs 65.0 on MMLU-Pro
Choose DeepSeek R1 Distill Qwen 32B if:
  • • You have limited VRAM — it's a smaller model needing 20.6 GB vs 42.2 GB

Frequently asked questions

Which is better, DeepSeek R1 Distill Llama 70B or DeepSeek R1 Distill Qwen 32B?
DeepSeek R1 Distill Llama 70B has 70B parameters vs 32.5B for DeepSeek R1 Distill Qwen 32B, so DeepSeek R1 Distill Llama 70B is the larger model. DeepSeek R1 Distill Qwen 32B is more hardware-efficient, needing 20.6 GB at Q4_K_M vs 42.2 GB. DeepSeek R1 Distill Qwen 32B runs on more GPUs natively (51 vs 38). On MMLU-Pro, DeepSeek R1 Distill Llama 70B scores higher (70.0 vs 65.0).
How much VRAM does DeepSeek R1 Distill Llama 70B need vs DeepSeek R1 Distill Qwen 32B?
At Q4_K_M quantization with 8k context, DeepSeek R1 Distill Llama 70B needs approximately 42.2 GB of VRAM, while DeepSeek R1 Distill Qwen 32B needs 20.6 GB. At FP16, DeepSeek R1 Distill Llama 70B requires 159.8 GB vs 75.2 GB for DeepSeek R1 Distill Qwen 32B.
Can you run DeepSeek R1 Distill Llama 70B on the same GPUs as DeepSeek R1 Distill Qwen 32B?
Yes, 38 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA H100 80GB, NVIDIA A100 80GB. However, no GPU can run DeepSeek R1 Distill Llama 70B without also fitting DeepSeek R1 Distill Qwen 32B, and 13 GPUs can run DeepSeek R1 Distill Qwen 32B but not DeepSeek R1 Distill Llama 70B.
What is the difference between DeepSeek R1 Distill Llama 70B and DeepSeek R1 Distill Qwen 32B?
DeepSeek R1 Distill Llama 70B has 70B parameters (dense) with a 125k context window. DeepSeek R1 Distill Qwen 32B has 32.5B parameters (dense) with a 125k context window.
Which model fits in 24 GB of VRAM, DeepSeek R1 Distill Llama 70B or DeepSeek R1 Distill Qwen 32B?
Only DeepSeek R1 Distill Qwen 32B fits in 24 GB at Q4_K_M (20.6 GB). DeepSeek R1 Distill Llama 70B needs 42.2 GB, requiring a larger GPU.
Full DeepSeek R1 Distill Llama 70B page →Full DeepSeek R1 Distill Qwen 32B page →Check your hardware →