Meta Llama 3 8B Instruct vs Qwen2.5 7B Instruct
Qwen2.5 7B Instruct leads llmrun Score 65.1 to 61.7 (ranges overlap); both fit 24 GB at Q4_K_M.
Model B · Alibaba
Qwen2.5 7B Instruct7.6B · 32K context · Apache 2.0 · Sep 2024
Choose Qwen2.5 7B Instruct if you want…
Higher llmrun Score
65.1 vs 61.7, ranges overlap
Ahead on the benchmarks
4 of 5 shared boards
Also does function-calling
Meta Llama 3 8B Instruct doesn't list it
More permissive license
Apache 2.0 vs Llama 3 Community
Newer release
Sep 2024 vs Apr 2024
Meta Llama 3 8B Instruct: no clear edge over Qwen2.5 7B Instruct in the data we have.
On your hardware
Each model at its default quant (Q4_K_M), a smaller one when it must. Estimates, ±20%.
8 GB
RTX 4060 · 8 GB tier
Meta Llama 3 8B Instruct
Q4_K_M · ~33 tok/s
7.9 GB · up to 16K
Qwen2.5 7B Instruct
Q4_K_M · ~35 tok/s
5.8 GB · up to 32K
12 GB
RTX 3060 12GB · 12 GB tier
Meta Llama 3 8B Instruct
Q4_K_M · ~44 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~47 tok/s
5.8 GB · up to 32K
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Meta Llama 3 8B Instruct
Q4_K_M · ~55 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~58 tok/s
5.8 GB · up to 32K
24 GBreference
RTX 4090 · 24 GB tier
Meta Llama 3 8B Instruct
Q4_K_M · ~124 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~131 tok/s
5.8 GB · up to 32K
32 GB
RTX 5090 · 32 GB tier
Meta Llama 3 8B Instruct
Q4_K_M · ~220 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~233 tok/s
5.8 GB · up to 32K
48 GB
RTX A6000 · 48 GB tier
Meta Llama 3 8B Instruct
Q4_K_M · ~94 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~100 tok/s
5.8 GB · up to 32K
Mac 32 GB
Mac Mini M4 · Macs
Meta Llama 3 8B Instruct
Q4_K_M · ~16 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~17 tok/s
5.8 GB · up to 32K
Mac 64 GB
Mac Studio M4 Max · Macs
Meta Llama 3 8B Instruct
Q4_K_M · ~72 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~77 tok/s
5.8 GB · up to 32K
Mac 128 GB
Mac Studio M4 Max · Macs
Meta Llama 3 8B Instruct
Q4_K_M · ~72 tok/s
7.9 GB · up to 32K
Qwen2.5 7B Instruct
Q4_K_M · ~77 tok/s
5.8 GB · up to 32K
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Meta Llama 3 8B Instruct
Qwen2.5 7B Instruct
Reasoning
Meta Llama 3 8B Instruct
Qwen2.5 7B Instruct
Meta Llama 3 8B Instruct · #89 of 92 open models · #32 of 34 that fit 24 GB
Qwen2.5 7B Instruct · #86 of 92 open models · #29 of 34 that fit 24 GB
Benchmarks
5 shared boards: Meta Llama 3 8B Instruct leads 0, Qwen2.5 7B Instruct leads 4 · Benchmarks imported Oct 2026
Meta Llama 3 8B Instruct
26.1%#88/97 open
IndependentEpoch AI · Apr 2024
Qwen2.5 7B Instruct
35.5%#74/97 open
IndependentEpoch AI · Sep 2024
Meta Llama 3 8B Instruct
1.9%#75/85 open
IndependentEpoch AI · Apr 2024
Qwen2.5 7B Instruct
2.5%#74/85 open
IndependentEpoch AI · Sep 2024
Meta Llama 3 8B Instruct
68.8%#30/85 open
Lab-reportedEpoch AI · Apr 2024
Qwen2.5 7B Instruct
72.9%#24/85 open
Lab-reportedEpoch AI · Sep 2024
Meta Llama 3 8B Instruct
0.0%#59/67 open
IndependentEpoch AI · Apr 2024
Qwen2.5 7B Instruct
0.0%#64/67 open
IndependentEpoch AI · Sep 2024
Meta Llama 3 8B Instruct
43.9%#66/68 open
Lab-reportedEpoch AI · Apr 2024
Qwen2.5 7B Instruct
47.7%#64/68 open
Lab-reportedEpoch AI · Sep 2024
10 more boards (other shared and single-model boards)
Only Meta Llama 3 8B Instruct (8)
- LMArena Text1223.6
- MMLU-Pro41.0%
- MATH Level 56.1%
- ForecastBench58.6
- WinoGrande65.0%
- ARC Challenge82.8%
- OpenBookQA82.6%
- TriviaQA67.7%
VRAM by quantization
Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.
Q2_K
Meta Llama 3 8B Instruct
3.8 GB3.2 GB file
32K 9.3 GB · 128K 26.9 GB
Qwen2.5 7B Instruct
3.7 GB3.0 GB file
32K 5.4 GB · 128K —
Q3_K_S
Meta Llama 3 8B Instruct
3.9 GB3.7 GB file
32K 9.4 GB · 128K 27.0 GB
Qwen2.5 7B Instruct
3.8 GB3.5 GB file
32K 5.5 GB · 128K —
Q3_K_M
Meta Llama 3 8B Instruct
4.3 GB4.0 GB file
32K 9.8 GB · 128K 27.4 GB
Qwen2.5 7B Instruct
4.1 GB3.8 GB file
32K 5.9 GB · 128K —
Q4_0
Meta Llama 3 8B Instruct
4.4 GB4.7 GB file
32K 9.9 GB · 128K 27.5 GB
Qwen2.5 7B Instruct
4.2 GB4.4 GB file
32K 6.0 GB · 128K —
Q4_K_M
Meta Llama 3 8B Instruct
5.3 GB4.9 GB file
32K 10.8 GB · 128K 28.4 GB
Qwen2.5 7B Instruct
5.0 GB4.7 GB file
32K 6.8 GB · 128K —
Q5_K_M
Meta Llama 3 8B Instruct
6.3 GB5.7 GB file
32K 11.8 GB · 128K 29.4 GB
Qwen2.5 7B Instruct
5.8 GB5.4 GB file
32K 7.6 GB · 128K —
Q6_K
Meta Llama 3 8B Instruct
7.3 GB6.6 GB file
32K 12.8 GB · 128K 30.4 GB
Qwen2.5 7B Instruct
6.7 GB6.3 GB file
32K 8.5 GB · 128K —
Q8_0
Meta Llama 3 8B Instruct
8.8 GB8.5 GB file
32K 14.3 GB · 128K 32.0 GB
Qwen2.5 7B Instruct
8.0 GB8.1 GB file
32K 9.8 GB · 128K —
20 more quants
IQ2_XXS
Meta Llama 3 8B Instruct
2.4 GB2.4 GB file
32K 7.9 GB · 128K 25.6 GB
Qwen2.5 7B Instruct
2.5 GB2.3 GB file
32K 4.3 GB · 128K —
IQ2_XS
Meta Llama 3 8B Instruct
2.7 GB2.6 GB file
32K 8.2 GB · 128K 25.8 GB
Qwen2.5 7B Instruct
2.7 GB2.5 GB file
32K 4.5 GB · 128K —
IQ2_S
Meta Llama 3 8B Instruct
2.8 GB2.8 GB file
32K 8.3 GB · 128K 25.9 GB
Qwen2.5 7B Instruct
2.8 GB2.6 GB file
32K 4.6 GB · 128K —
IQ2_M
Meta Llama 3 8B Instruct
3.0 GB2.9 GB file
32K 8.5 GB · 128K 26.1 GB
Qwen2.5 7B Instruct
3.0 GB2.8 GB file
32K 4.8 GB · 128K —
IQ3_XXS
Meta Llama 3 8B Instruct
3.4 GB3.3 GB file
32K 8.9 GB · 128K 26.5 GB
Qwen2.5 7B Instruct
3.4 GB3.1 GB file
32K 5.1 GB · 128K —
Q2_K_S
Meta Llama 3 8B Instruct
3.5 GB3.0 GB file
32K 9.0 GB · 128K 26.7 GB
Qwen2.5 7B Instruct
3.5 GB2.8 GB file
32K 5.2 GB · 128K —
IQ3_XS
Meta Llama 3 8B Instruct
3.6 GB3.5 GB file
32K 9.1 GB · 128K 26.8 GB
Qwen2.5 7B Instruct
3.6 GB3.3 GB file
32K 5.3 GB · 128K —
IQ3_S
Meta Llama 3 8B Instruct
3.8 GB3.7 GB file
32K 9.3 GB · 128K 26.9 GB
Qwen2.5 7B Instruct
3.7 GB3.5 GB file
32K 5.4 GB · 128K —
IQ3_M
Meta Llama 3 8B Instruct
4.0 GB3.8 GB file
32K 9.5 GB · 128K 27.1 GB
Qwen2.5 7B Instruct
3.8 GB3.6 GB file
32K 5.6 GB · 128K —
Q3_K_L
Meta Llama 3 8B Instruct
4.5 GB4.3 GB file
32K 10.0 GB · 128K 27.7 GB
Qwen2.5 7B Instruct
4.3 GB4.1 GB file
32K 6.1 GB · 128K —
IQ4_XS
Meta Llama 3 8B Instruct
4.8 GB4.4 GB file
32K 10.3 GB · 128K 27.9 GB
Qwen2.5 7B Instruct
4.5 GB4.2 GB file
32K 6.3 GB · 128K —
IQ4_NL
Meta Llama 3 8B Instruct
5.0 GB4.7 GB file
32K 10.5 GB · 128K 28.1 GB
Qwen2.5 7B Instruct
4.7 GB4.4 GB file
32K 6.5 GB · 128K —
Q4_1
Meta Llama 3 8B Instruct
5.0 GB5.1 GB file
32K 10.5 GB · 128K 28.1 GB
Qwen2.5 7B Instruct
4.7 GB4.9 GB file
32K 6.5 GB · 128K —
Q4_K_S
Meta Llama 3 8B Instruct
5.0 GB4.7 GB file
32K 10.5 GB · 128K 28.1 GB
Qwen2.5 7B Instruct
4.7 GB4.5 GB file
32K 6.5 GB · 128K —
Q4_K_L
Meta Llama 3 8B Instruct
not listed
Qwen2.5 7B Instruct
5.1 GB5.1 GB file
32K 6.8 GB · 128K —
Q5_0
Meta Llama 3 8B Instruct
5.5 GB5.6 GB file
32K 11.0 GB · 128K 28.6 GB
Qwen2.5 7B Instruct
5.2 GB5.3 GB file
32K 6.9 GB · 128K —
Q5_1
Meta Llama 3 8B Instruct
6.1 GB6.1 GB file
32K 11.6 GB · 128K 29.2 GB
Qwen2.5 7B Instruct
5.7 GB5.8 GB file
32K 7.4 GB · 128K —
Q5_K_S
Meta Llama 3 8B Instruct
6.1 GB5.6 GB file
32K 11.6 GB · 128K 29.2 GB
Qwen2.5 7B Instruct
5.7 GB5.3 GB file
32K 7.4 GB · 128K —
Q5_K_L
Meta Llama 3 8B Instruct
not listed
Qwen2.5 7B Instruct
5.9 GB5.8 GB file
32K 7.7 GB · 128K —
BF16
Meta Llama 3 8B Instruct
17.7 GB~16.1 GB file
32K 23.2 GB · 128K 40.8 GB
Qwen2.5 7B Instruct
15.7 GB~15.2 GB file
32K 17.4 GB · 128K —
Meta Llama 3 8B Instruct
Ollama · Q4_K_M
ollama run hf.co/MaziyarPanahi/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_MQwen2.5 7B Instruct
Ollama · Q4_K_M
ollama run hf.co/bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M| Spec | Meta Llama 3 8B Instruct | Qwen2.5 7B Instruct |
|---|---|---|
| Publisher | Meta | Alibaba |
| Parameters | 8.0B | 7.6B |
| Architecture | — | Qwen2ForCausalLM |
| Context | — | 32K tokens |
| Modalities | Chat | Chat, Function-calling |
| License | Llama 3 Community | Apache 2.0 |
| Released | Apr 2024 | Sep 2024 |
Frequently Asked Questions
Which is better, Meta Llama 3 8B Instruct or Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct leads llmrun Score 65.1 to 61.7 (ranges overlap); both fit 24 GB at Q4_K_M. Choose Qwen2.5 7B Instruct for higher llmrun Score and ahead on the benchmarks.
Which needs less VRAM, Meta Llama 3 8B Instruct or Qwen2.5 7B Instruct?
At Q4_K_M, Meta Llama 3 8B Instruct requires 5.3 GB while Qwen2.5 7B Instruct needs 5.0 GB, making Qwen2.5 7B Instruct the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 124 tok/s for Meta Llama 3 8B Instruct (Q4_K_M) and 131 tok/s for Qwen2.5 7B Instruct (Q4_K_M), so Qwen2.5 7B Instruct is faster. Estimates, ±20%.
Can I run Meta Llama 3 8B Instruct or Qwen2.5 7B Instruct on a 16 GB GPU?
Meta Llama 3 8B Instruct fits at Q4_K_M; Qwen2.5 7B Instruct fits at Q4_K_M.