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Llama 4 Scout 109B vs Qwen3 235B-A22B (MoE)

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

Quick verdict

Llama 4 Scout 109B is more hardware-efficient — it needs 71.7 GB at Q4_K_M vs 149.9 GB for Qwen3 235B-A22B (MoE), fitting on 39 GPUs natively.

VRAM at each quantization (8k context)

QuantLlama 4 Scout 109BQwen3 235B-A22B (MoE)Diff
FP32491.3 GB1054.6 GB-53%
BF16247.2 GB528.2 GB-53%
FP16247.2 GB528.2 GB-53%
Q8_0125.1 GB265.0 GB-53%
Q6_K103.1 GB217.6 GB-53%
Q5_K_M81.6 GB171.3 GB-52%
Q4_K_M71.7 GB149.9 GB-52%
Q3_K_M55.5 GB114.9 GB-52%
Q2_K43.2 GB88.4 GB-51%
NVFP464.0 GB133.4 GB-52%

Diff is Llama 4 Scout 109B relative to Qwen3 235B-A22B (MoE). Green = lower VRAM (fits more GPUs).

Model specifications

SpecLlama 4 Scout 109BQwen3 235B-A22B (MoE)
OrgMetaAlibaba
Parameters109B235B
ArchitectureMoE (17B active)MoE (22B active)
Context9766k tokens128k tokens
Modalitiestext, visiontext
LicenseLlama 4 CommunityApache 2.0
CommercialYesYes
Released2025-04-052025-04-29
GPUs (native)39 / 10720 / 107

Benchmark scores

BenchmarkLlama 4 Scout 109BQwen3 235B-A22B (MoE)
MMLU-Pro74.384.4

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

GPUs that run only Llama 4 Scout 109B(19)

GPUs that run only Qwen3 235B-A22B (MoE)(0)

Every GPU that runs Qwen3 235B-A22B (MoE) also runs Llama 4 Scout 109B.

GPUs that run both natively(20)

Which should you use?

Choose Llama 4 Scout 109B if:
  • • You have limited VRAM — it's a smaller model needing 71.7 GB vs 149.9 GB
  • • Long context matters — it supports 9766k tokens vs 128k
  • • You need vision/image understanding
Choose Qwen3 235B-A22B (MoE) if:
  • • You want maximum capability and have a 150 GB+ GPU
  • • Benchmark quality matters — scores 84.4 vs 74.3 on MMLU-Pro
  • • You need chain-of-thought reasoning

Frequently asked questions

Which is better, Llama 4 Scout 109B or Qwen3 235B-A22B (MoE)?
Llama 4 Scout 109B has 109B parameters vs 235B for Qwen3 235B-A22B (MoE), so Qwen3 235B-A22B (MoE) is the larger model. Llama 4 Scout 109B is more hardware-efficient, needing 71.7 GB at Q4_K_M vs 149.9 GB. Llama 4 Scout 109B runs on more GPUs natively (39 vs 20). On MMLU-Pro, Qwen3 235B-A22B (MoE) scores higher (84.4 vs 74.3).
How much VRAM does Llama 4 Scout 109B need vs Qwen3 235B-A22B (MoE)?
At Q4_K_M quantization with 8k context, Llama 4 Scout 109B needs approximately 71.7 GB of VRAM, while Qwen3 235B-A22B (MoE) needs 149.9 GB. At FP16, Llama 4 Scout 109B requires 247.2 GB vs 528.2 GB for Qwen3 235B-A22B (MoE).
Can you run Llama 4 Scout 109B on the same GPUs as Qwen3 235B-A22B (MoE)?
Yes, 20 GPUs can run both natively in VRAM, including NVIDIA RTX Pro 6000, NVIDIA DGX Spark (128GB), AMD Instinct MI300X. However, 19 GPUs can run Llama 4 Scout 109B but not Qwen3 235B-A22B (MoE), and no GPU can run Qwen3 235B-A22B (MoE) without also fitting Llama 4 Scout 109B.
What is the difference between Llama 4 Scout 109B and Qwen3 235B-A22B (MoE)?
Llama 4 Scout 109B has 109B parameters (17B active, MoE) with a 9766k context window. Qwen3 235B-A22B (MoE) has 235B parameters (22B active, MoE) with a 128k context window. Licensing differs: Llama 4 Scout 109B is Llama 4 Community while Qwen3 235B-A22B (MoE) is Apache 2.0.
Which model fits in 24 GB of VRAM, Llama 4 Scout 109B or Qwen3 235B-A22B (MoE)?
Neither fits in 24 GB at Q4_K_M — Llama 4 Scout 109B needs 71.7 GB and Qwen3 235B-A22B (MoE) needs 149.9 GB. Both require at least a 48 GB GPU.
Full Llama 4 Scout 109B page →Full Qwen3 235B-A22B (MoE) page →Check your hardware →