Meta Llama 3 70B Instruct vs Qwen3.8 27B
Qwen3.8 27B leads llmrun Score 122.1 to 74.3; only Qwen3.8 27B fits 24 GB (Q4_K_M); Meta Llama 3 70B Instruct needs 28 GB even at its smallest quant.
Model B · Alibaba
Qwen3.8 27B27.8B · 256K context · Apache 2.0 · Aug 2026
Choose Meta Llama 3 70B Instruct if you want…
Also does chat
Qwen3.8 27B doesn't list it
Choose Qwen3.8 27B if you want…
Higher llmrun Score
122.1 vs 74.3
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Meta Llama 3 70B Instruct needs 28 GB at its smallest quant
Fits a Mac 32 GB
Q4_K_M · 17.9 GB; Meta Llama 3 70B Instruct needs 28 GB at its smallest quant
Lighter on memory
17.4 vs 46.6 GB at Q4_K_M
Also does vision, function-calling
Meta Llama 3 70B Instruct doesn't list it
More permissive license
Apache 2.0 vs Llama 3 Community
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 70B Instruct
Doesn't fit
smallest quant needs 28 GB
Qwen3.8 27B
Doesn't fit
smallest quant needs 8.8 GB
12 GB
RTX 3060 12GB · 12 GB tier
Meta Llama 3 70B Instruct
Doesn't fit
smallest quant needs 28 GB
Qwen3.8 27B
IQ3_XXS · ~20 tok/s
12 GB · up to 16Kfits
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Meta Llama 3 70B Instruct
Doesn't fit
smallest quant needs 28 GB
Qwen3.8 27B
Q3_K_L · ~19 tok/s
15.4 GB · up to 16Kfits
24 GBreference
RTX 4090 · 24 GB tier
Meta Llama 3 70B Instruct
Doesn't fit
smallest quant needs 28 GB
Qwen3.8 27B
Q4_K_M · ~38 tok/s
17.9 GB · up to 64Kfits
32 GB
RTX 5090 · 32 GB tier
Meta Llama 3 70B Instruct
IQ2_XS · ~50 tok/s
28 GB · up to 16K
Qwen3.8 27B
Q4_K_M · ~67 tok/s
17.9 GB · up to 256Kmore headroom
48 GB
RTX A6000 · 48 GB tier
Meta Llama 3 70B Instruct
Q4_K_M · ~11 tok/stight
51.3 GB · up to 4K
Qwen3.8 27B
Q4_K_M · ~29 tok/s
17.9 GB · up to 256Kmore headroom
Mac 32 GB
Mac Mini M4 · Macs
Meta Llama 3 70B Instruct
IQ2_XS · ~4 tok/s
28 GB · up to 16K
Qwen3.8 27B
Q4_K_M · ~5 tok/s
17.9 GB · up to 128Kmore headroom
Mac 64 GB
Mac Studio M4 Max · Macs
Meta Llama 3 70B Instruct
Q4_K_M · ~8 tok/s
51.3 GB · up to 32K
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256Kfaster
Mac 128 GB
Mac Studio M4 Max · Macs
Meta Llama 3 70B Instruct
Q4_K_M · ~8 tok/s
51.3 GB · up to 32K
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256Kfaster
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Meta Llama 3 70B Instruct
Qwen3.8 27B
Coding
Meta Llama 3 70B Instruct
no data
Qwen3.8 27B
Agents
Meta Llama 3 70B Instruct
no data
Qwen3.8 27B
Math
Meta Llama 3 70B Instruct
no data
Qwen3.8 27B
Science
Meta Llama 3 70B Instruct
no data
Qwen3.8 27B
Reasoning
Meta Llama 3 70B Instruct
no data
Qwen3.8 27B
Meta Llama 3 70B Instruct · #89 of 100 open models · #39 of 49 that fit ≤64 GB
Qwen3.8 27B · #11 of 100 open models · #1 of 35 that fit 24 GB
Benchmarks
1 shared board: Meta Llama 3 70B Instruct leads 0, Qwen3.8 27B leads 1 · Benchmarks imported Oct 2026
Meta Llama 3 70B Instruct
54.2%#56/68 open
Lab-reportedEpoch AI · Apr 2024
Qwen3.8 27B
88.0%#9/68 open
Lab-reportedEpoch AI · Aug 2026
25 more boards (other shared and single-model boards)
Meta Llama 3 70B Instruct
1276.6#119/187 open
ArenaLMArena · Oct 2026
Qwen3.8 27B
1437.8#22/187 open
ArenaLMArena · Oct 2026
Only Meta Llama 3 70B Instruct (5)
- GPQA Diamond40.6%
- AIME 2024/20254.3%
- MMLU-Pro56.2%
- MATH Level 522.6%
- MMLU79.3%
Only Qwen3.8 27B (19)
- LiveBench Coding75.7
- LiveBench Reasoning80.0
- LMArena WebDev1593.2
- LiveBench Math86.2
- ARC-AGI-242.4%
- SciCode46.6%
- ARC-AGI87.5%
- APEX-Agents47.5%
- CritPt5.4%
- LiveBench 2026 Reasoning80.0
- LMCA41.4%
- LiveBench 2026 Browser32.0
- LiveBench 2026 Data Analysis76.6
- LiveBench 2026 Coding86.8
- LiveBench 2026 Long-Horizon27.9
- Surface Evolver Bench45.0%
- LiveBench 2026 Design75.9
- ProofBench16.0%
- LiveBench 2026 Research59.4
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 70B Instruct
33.0 GB26.4 GB file
32K 43.1 GB · 128K 75.5 GB
Qwen3.8 27B
12.6 GB10.8 GB file
32K 13.9 GB · 128K 19.3 GB
Q3_K_S
Meta Llama 3 70B Instruct
34.0 GB30.9 GB file
32K 44.1 GB · 128K 76.4 GB
Qwen3.8 27B
12.9 GB12.7 GB file
32K 14.2 GB · 128K 19.6 GB
Q3_K_M
Meta Llama 3 70B Instruct
37.8 GB34.3 GB file
32K 48.0 GB · 128K 80.3 GB
Qwen3.8 27B
14.3 GB13.4 GB file
32K 15.6 GB · 128K 21.0 GB
Q4_0
Meta Llama 3 70B Instruct
38.8 GB40.0 GB file
32K 48.9 GB · 128K 81.3 GB
Qwen3.8 27B
14.6 GB~13.9 GB file
32K 16.0 GB · 128K 21.4 GB
Q4_K_M
Meta Llama 3 70B Instruct
46.6 GB42.5 GB file
32K 56.7 GB · 128K 89.1 GB
Qwen3.8 27B
17.4 GB16.5 GB file
32K 18.8 GB · 128K 24.1 GB
Q5_K_M
Meta Llama 3 70B Instruct
55.3 GB50.0 GB file
32K 65.4 GB · 128K 97.8 GB
Qwen3.8 27B
20.5 GB19.8 GB file
32K 21.9 GB · 128K 27.3 GB
Q6_K
Meta Llama 3 70B Instruct
64.0 GB57.9 GB file
32K 74.2 GB · 128K 107 GB
Qwen3.8 27B
23.7 GB22.0 GB file
32K 25.0 GB · 128K 30.4 GB
Q8_0
Meta Llama 3 70B Instruct
77.6 GB75.0 GB file
32K 87.7 GB · 128K 120 GB
Qwen3.8 27B
28.5 GB29.0 GB file
32K 29.9 GB · 128K 35.2 GB
19 more quants
IQ2_XXS
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
8.4 GB7.3 GB file
32K 9.7 GB · 128K 15.1 GB
IQ2_XS
Meta Llama 3 70B Instruct
23.3 GB21.1 GB file
32K 33.4 GB · 128K 65.8 GB
Qwen3.8 27B
9.1 GB9.1 GB file
32K 10.4 GB · 128K 15.8 GB
IQ2_S
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
9.4 GB8.4 GB file
32K 10.8 GB · 128K 16.1 GB
IQ2_M
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
10.1 GB10.5 GB file
32K 11.5 GB · 128K 16.8 GB
IQ3_XXS
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
11.5 GB10.9 GB file
32K 12.9 GB · 128K 18.2 GB
IQ3_XS
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
12.2 GB10.4 GB file
32K 13.6 GB · 128K 18.9 GB
IQ3_S
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
12.6 GB12.0 GB file
32K 13.9 GB · 128K 19.3 GB
IQ3_M
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
13.3 GB14.9 GB file
32K 14.6 GB · 128K 20.0 GB
Q3_K_L
Meta Llama 3 70B Instruct
39.8 GB37.1 GB file
32K 49.9 GB · 128K 82.3 GB
Qwen3.8 27B
15.0 GB14.1 GB file
32K 16.3 GB · 128K 21.7 GB
IQ4_XS
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
15.7 GB14.3 GB file
32K 17.0 GB · 128K 22.4 GB
IQ4_NL
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
16.4 GB17.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_1
Meta Llama 3 70B Instruct
43.7 GB44.3 GB file
32K 53.8 GB · 128K 86.2 GB
Qwen3.8 27B
16.4 GB17.5 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_S
Meta Llama 3 70B Instruct
43.7 GB40.3 GB file
32K 53.8 GB · 128K 86.2 GB
Qwen3.8 27B
16.4 GB15.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_L
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
17.8 GB18.8 GB file
32K 19.1 GB · 128K 24.5 GB
Q5_0
Meta Llama 3 70B Instruct
48.5 GB48.7 GB file
32K 58.6 GB · 128K 91.0 GB
Qwen3.8 27B
not listed
Q5_1
Meta Llama 3 70B Instruct
53.4 GB53.0 GB file
32K 63.5 GB · 128K 95.9 GB
Qwen3.8 27B
not listed
Q5_K_S
Meta Llama 3 70B Instruct
53.4 GB48.7 GB file
32K 63.5 GB · 128K 95.9 GB
Qwen3.8 27B
19.9 GB18.7 GB file
32K 21.2 GB · 128K 26.6 GB
Q5_K_L
Meta Llama 3 70B Instruct
not listed
Qwen3.8 27B
20.9 GB21.5 GB file
32K 22.2 GB · 128K 27.6 GB
BF16
Meta Llama 3 70B Instruct
155 GB~141.1 GB file
32K 165 GB · 128K 198 GB
Qwen3.8 27B
56.3 GB54.7 GB file
32K 57.7 GB · 128K 63.0 GB
Meta Llama 3 70B Instruct
Ollama · Q4_K_M
ollama run hf.co/second-state/Meta-Llama-3-70B-Instruct-GGUF:Q4_K_MQwen3.8 27B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_M| Spec | Meta Llama 3 70B Instruct | Qwen3.8 27B |
|---|---|---|
| Publisher | Meta | Alibaba |
| Parameters | 70.6B | 27.8B |
| Architecture | — | Qwen3_5ForConditionalGeneration |
| Context | — | 256K tokens |
| Modalities | Chat | Vision, Function-calling |
| License | Llama 3 Community | Apache 2.0 |
| Released | Apr 2024 | Aug 2026 |
Frequently Asked Questions
Which is better, Meta Llama 3 70B Instruct or Qwen3.8 27B?
Qwen3.8 27B leads llmrun Score 122.1 to 74.3; only Qwen3.8 27B fits 24 GB (Q4_K_M); Meta Llama 3 70B Instruct needs 28 GB even at its smallest quant. Choose Meta Llama 3 70B Instruct for also does chat; choose Qwen3.8 27B for higher llmrun Score and fits a 12 GB GPU.
Which needs less VRAM, Meta Llama 3 70B Instruct or Qwen3.8 27B?
At Q4_K_M, Meta Llama 3 70B Instruct requires 46.6 GB while Qwen3.8 27B needs 17.4 GB, making Qwen3.8 27B the easier model to run on your local setup.
Can I run Meta Llama 3 70B Instruct or Qwen3.8 27B on a 16 GB GPU?
Meta Llama 3 70B Instruct does not fit (smallest quant needs 28 GB); Qwen3.8 27B fits at Q3_K_L.