Qwen 3 8B vs Llama 3.1 8B
Side-by-side specs, benchmarks, and a verdict by use case.
Updated 2026-07-13
| Spec | Qwen 3 8B | Llama 3.1 8B |
|---|---|---|
| Parameters | 8B | 8B |
| Author | Alibaba | Meta |
| License | Apache 2.0 | Llama 3 Community |
| Context window | 0k | 0k |
| VRAM at Q4 | 5 GB | 6 GB |
| VRAM at Q5 | 6 GB | 7 GB |
| VRAM at Q8 | 9 GB | 10 GB |
| VRAM at FP16 | 16 GB | 18 GB |
| Use cases | chat, general, reasoning, multilingual | chat, general |
Verdict
Both models sit in a similar size class. The pick depends on tags, license, and benchmarks rather than raw parameter count.
For unambiguous commercial use, Qwen 3 8B has the safer license (Apache 2.0) compared to Llama 3 Community.
The two models at a glance
About Qwen 3 8B
Alibaba's 8B dense model with a toggleable thinking mode and broad multilingual coverage. Punches well above its weight for an 8B and runs comfortably on a single consumer GPU. Strengths: Hybrid thinking/fast modes switchable per request, Strong multilingual performance across 119 languages, Up to 131K context via YaRN (32K native), Apache 2.0 — clean commercial use.
About Llama 3.1 8B
Meta's Llama 3.1 8B, the open-weight benchmark of 2024. A 128k context, well-behaved instruction follower with the largest ecosystem in the open-source world. Strengths: 128k context window, Strong instruction following and coding, Enormous ecosystem of fine-tunes and integrations, Solid quality-to-size ratio.
How they compare
Qwen 3 8B comes from Alibaba and Llama 3.1 8B from Meta, they belong to the Qwen and Llama 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.
Qwen 3 8B and Llama 3.1 8B share the same 8B parameter class. At Q4, Qwen 3 8B fits in about 5 GB of VRAM versus 6 GB for the other — a 1 GB difference that matters on consumer GPUs.
Where they overlap on benchmarks, Qwen 3 8B takes GPQA with 60 against 46.7 — a decisive 13.3-point margin. For workloads weighted toward that benchmark, Qwen 3 8B is the stronger default.
On a typical mid-range GPU, Qwen 3 8B pushes roughly 35 tokens/sec versus 30, so it is the more responsive choice for interactive or high-volume use.
Memory, quantization & throughput
Across quantization levels, Qwen 3 8B requires Q4 ≈ 5 GB, Q5 ≈ 6 GB, Q8 ≈ 9 GB, FP16 ≈ 16 GB, while Llama 3.1 8B requires Q4 ≈ 6 GB, Q5 ≈ 7 GB, Q8 ≈ 10 GB, FP16 ≈ 18 GB. In practice Qwen 3 8B fits an 8 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 8B needs roughly 10 GB of system RAM to run on CPU and Llama 3.1 8B about 10 GB — workable for offline use but far slower than GPU inference. On a mid-range GPU you can expect on the order of 35 tokens/sec from Qwen 3 8B and 30 from Llama 3.1 8B, scaling up to 90 and 80 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 8B or Llama 3.1 8B to the card you actually own:
- On a 8 GB GPU: Qwen 3 8B runs at Q5 (6 GB); Llama 3.1 8B runs at Q5 (7 GB).
- On a 12 GB GPU: Qwen 3 8B runs at Q8 (9 GB); Llama 3.1 8B runs at Q8 (10 GB).
- On a 16 GB GPU: Qwen 3 8B runs at FP16 (16 GB); Llama 3.1 8B runs at Q8 (10 GB).
- On a 24 GB GPU: Qwen 3 8B runs at FP16 (16 GB); Llama 3.1 8B runs at FP16 (18 GB).
Benchmark scores
Reported benchmarks for Qwen 3 8B: MMLU-Pro 68.7, GPQA 60, LiveCodeBench 54.4.
Reported benchmarks for Llama 3.1 8B: MMLU 73, HumanEval 72.6, GPQA 46.7.
Bottom line: which should you pick?
- Pick Qwen 3 8B if you need a permissive (Apache 2.0) license for commercial deployment.
- Pick Qwen 3 8B if GPQA performance is your priority (60 vs 46.7).
- Pick Qwen 3 8B if your workload is multilingual, reasoning.
Which GPU should you buy to run Llama 3.1 8B?
To run Llama 3.1 8B locally at Q4, you need ~6 GB of VRAM. The best value for this is a RTX 5060 (8 GB VRAM).
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Frequently asked questions
What is the difference between Qwen 3 8B and Llama 3.1 8B?
The headline differences: both are 8B models; they ship under different licenses (Apache 2.0 vs Llama 3 Community). Below we break down VRAM by quantization, benchmark scores, and a use-case verdict so you can pick the right one.
Can Qwen 3 8B and Llama 3.1 8B run on a 24 GB GPU?
At a Q4 quantization, Qwen 3 8B needs about 5 GB of VRAM and fits comfortably on a 24 GB GPU; Llama 3.1 8B needs about 6 GB and fits comfortably on a 24 GB GPU. Qwen 3 8B is the lighter option for tight VRAM budgets.
Is Qwen 3 8B or Llama 3.1 8B more capable?
On GPQA, Qwen 3 8B scores higher (60 vs 46.7), a 13.3-point advantage on this benchmark.
Which license is safer for commercial use, Qwen 3 8B or Llama 3.1 8B?
Qwen 3 8B ships under Apache 2.0, a permissive license with no usage restrictions, whereas the other is under Llama 3 Community — check its terms before commercial deployment.