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Qwen3 32B vs Llama 3.3 70B Instruct

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

Quick verdict

Qwen3 32B is more hardware-efficient — it needs 19.9 GB at Q4_K_M vs 42.2 GB for Llama 3.3 70B Instruct, fitting on 51 GPUs natively.

VRAM at each quantization (8k context)

QuantQwen3 32BLlama 3.3 70B InstructDiff
FP1675.0 GB159.8 GB-53%
Q838.2 GB81.4 GB-53%
Q6_K29.1 GB61.8 GB-53%
Q5_K_M24.5 GB52.0 GB-53%
Q4_K_M19.9 GB42.2 GB-53%
Q3_K_M16.2 GB34.4 GB-53%
Q2_K12.5 GB26.5 GB-53%

Diff is Qwen3 32B relative to Llama 3.3 70B Instruct. Green = lower VRAM (fits more GPUs).

Model specifications

SpecQwen3 32BLlama 3.3 70B Instruct
OrgAlibabaMeta
Parameters32.8B70B
ArchitectureDenseDense
Context128k tokens125k tokens
Modalitiestexttext
LicenseApache 2.0Llama 3.3 Community
CommercialYesYes
Released2025-04-292024-12-06
GPUs (native)51 / 6738 / 67

GPUs that run only Qwen3 32B(13)

GPUs that run only Llama 3.3 70B Instruct(0)

Every GPU that runs Llama 3.3 70B Instruct also runs Qwen3 32B.

GPUs that run both natively(38)

Which should you use?

Choose Qwen3 32B if:
  • • You have limited VRAM — it's a smaller model needing 19.9 GB vs 42.2 GB
  • • Long context matters — it supports 128k tokens vs 125k
  • • You need chain-of-thought reasoning
Choose Llama 3.3 70B Instruct if:
  • • You want maximum capability and have a 43 GB+ GPU

Frequently asked questions

Which is better, Qwen3 32B or Llama 3.3 70B Instruct?
Qwen3 32B has 32.8B parameters vs 70B for Llama 3.3 70B Instruct, so Llama 3.3 70B Instruct is the larger model. Qwen3 32B is more hardware-efficient, needing 19.9 GB at Q4_K_M vs 42.2 GB. Qwen3 32B runs on more GPUs natively (51 vs 38).
How much VRAM does Qwen3 32B need vs Llama 3.3 70B Instruct?
At Q4_K_M quantization with 8k context, Qwen3 32B needs approximately 19.9 GB of VRAM, while Llama 3.3 70B Instruct needs 42.2 GB. At FP16, Qwen3 32B requires 75.0 GB vs 159.8 GB for Llama 3.3 70B Instruct.
Can you run Qwen3 32B on the same GPUs as Llama 3.3 70B Instruct?
Yes, 38 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA H100 80GB, NVIDIA A100 80GB. However, 13 GPUs can run Qwen3 32B but not Llama 3.3 70B Instruct, and no GPU can run Llama 3.3 70B Instruct without also fitting Qwen3 32B.
What is the difference between Qwen3 32B and Llama 3.3 70B Instruct?
Qwen3 32B has 32.8B parameters (dense) with a 128k context window. Llama 3.3 70B Instruct has 70B parameters (dense) with a 125k context window. Licensing differs: Qwen3 32B is Apache 2.0 while Llama 3.3 70B Instruct is Llama 3.3 Community.
Which model fits in 24 GB of VRAM, Qwen3 32B or Llama 3.3 70B Instruct?
Only Qwen3 32B fits in 24 GB at Q4_K_M (19.9 GB). Llama 3.3 70B Instruct needs 42.2 GB, requiring a larger GPU.
Full Qwen3 32B page →Full Llama 3.3 70B Instruct page →Check your hardware →