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DeepSeek R1 Distill Llama 8B vs Qwen3 8B

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

Quick verdict

DeepSeek R1 Distill Llama 8B is more hardware-efficient: it needs 6.7 GB at its Q4_K_M build vs 6.8 GB for Qwen3 8B's Q4_K_M, fitting on 114 GPUs natively.

VRAM at each quantization (8k context)

FP32
DeepSeek R1 Distill Llama 8B
37.0 GB
Qwen3 8B
37.2 GB
BF16
DeepSeek R1 Distill Llama 8B
19.1 GB
Qwen3 8B
19.3 GB
FP16
DeepSeek R1 Distill Llama 8B
19.1 GB
Qwen3 8B
19.3 GB
Q8_0
DeepSeek R1 Distill Llama 8B
10.7 GB
Qwen3 8B
10.9 GB
Q6_K
DeepSeek R1 Distill Llama 8B
8.6 GB
Qwen3 8B
8.7 GB
Q5_K_M
DeepSeek R1 Distill Llama 8B
7.6 GB
Qwen3 8B
7.7 GB
Q4_K_M
DeepSeek R1 Distill Llama 8B
6.7 GB
Qwen3 8B
6.8 GB
Q3_K_M
DeepSeek R1 Distill Llama 8B
5.5 GB
Qwen3 8B
5.7 GB
Q2_K
DeepSeek R1 Distill Llama 8B
4.6 GB
Qwen3 8B
4.8 GB
NVFP4
DeepSeek R1 Distill Llama 8B
5.7 GB
Qwen3 8B
5.8 GB
QuantDeepSeek R1 Distill Llama 8BQwen3 8BDiff
FP3237.0 GB37.2 GB-0%
BF1619.1 GB19.3 GB-1%
FP1619.1 GB19.3 GB-1%
Q8_010.7 GB10.9 GB-1%
Q6_K8.6 GB8.7 GB-2%
Q5_K_M7.6 GB7.7 GB-2%
Q4_K_M6.7 GB6.8 GB-2%
Q3_K_M5.5 GB5.7 GB-3%
Q2_K4.6 GB4.8 GB-3%
NVFP45.7 GB5.8 GB-3%

Diff is DeepSeek R1 Distill Llama 8B relative to Qwen3 8B. Green = lower VRAM (fits more GPUs).

Model specifications

SpecDeepSeek R1 Distill Llama 8BQwen3 8B
OrgDeepSeekAlibaba
Parameters8B8B
ArchitectureDenseDense
Context125k tokens128k tokens
Modalitiestexttext
LicenseMITApache 2.0
CommercialYesYes
Released2025-01-202025-04-29
GPUs (native)114 / 119114 / 119

Benchmark scores

BenchmarkDeepSeek R1 Distill Llama 8BQwen3 8B
MMLU-Pro41.056.7
GPQA Diamond49.0N/A
MATH89.1N/A

Green = higher score (better). N/A = not yet available. ~ = inherited from a base model, not independently reported for that release itself.

GPUs that run only DeepSeek R1 Distill Llama 8B(0)

Every GPU that runs DeepSeek R1 Distill Llama 8B also runs Qwen3 8B.

GPUs that run only Qwen3 8B(0)

Every GPU that runs Qwen3 8B also runs DeepSeek R1 Distill Llama 8B.

GPUs that run both natively(114)

Which should you use?

Choose DeepSeek R1 Distill Llama 8B if:
  • No clear spec advantage over Qwen3 8B, see the benchmark and VRAM tables above.
Choose Qwen3 8B if:
  • • Long context matters: it supports 128k tokens vs 125k
  • • Benchmark quality matters: scores 56.7 vs 41.0 on MMLU-Pro
  • • It's the newer release (2025-04-29 vs 2025-01-20); check the benchmark table above for what actually improved

Frequently asked questions

Which is better, DeepSeek R1 Distill Llama 8B or Qwen3 8B?
DeepSeek R1 Distill Llama 8B is more hardware-efficient, needing 6.7 GB at its Q4_K_M build vs 6.8 GB for Qwen3 8B's Q4_K_M. On MMLU-Pro, Qwen3 8B scores higher (56.7 vs 41.0).
How much VRAM does DeepSeek R1 Distill Llama 8B need vs Qwen3 8B?
At 8k context, DeepSeek R1 Distill Llama 8B needs approximately 6.7 GB of VRAM at its Q4_K_M build, while Qwen3 8B needs 6.8 GB at its Q4_K_M build. At the largest build each ships, DeepSeek R1 Distill Llama 8B requires 19.1 GB (FP16) vs 19.3 GB (FP16) for Qwen3 8B.
Can you run DeepSeek R1 Distill Llama 8B on the same GPUs as Qwen3 8B?
Yes, 114 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 5080, NVIDIA RTX 5070 Ti. However, no GPU can run DeepSeek R1 Distill Llama 8B without also fitting Qwen3 8B, and no GPU can run Qwen3 8B without also fitting DeepSeek R1 Distill Llama 8B.
What is the difference between DeepSeek R1 Distill Llama 8B and Qwen3 8B?
DeepSeek R1 Distill Llama 8B has 8B parameters (dense) with a 125k context window. Qwen3 8B has 8B parameters (dense) with a 128k context window. Licensing differs: DeepSeek R1 Distill Llama 8B is MIT while Qwen3 8B is Apache 2.0.
Which model fits in 24 GB of VRAM, DeepSeek R1 Distill Llama 8B or Qwen3 8B?
Both fit in 24 GB of VRAM at their respective recommended builds: DeepSeek R1 Distill Llama 8B (Q4_K_M) needs 6.7 GB and Qwen3 8B (Q4_K_M) needs 6.8 GB.
Full DeepSeek R1 Distill Llama 8B page →Full Qwen3 8B page →Check your hardware →