Llama 3.1 8B Instruct vs Mistral Nemo Instruct 2407
Mistral Nemo Instruct 2407 leads llmrun Score 65.4 to 62.5 (ranges overlap); both fit 24 GB at Q4_K_M; Llama 3.1 8B Instruct is 1.5× faster on RTX 4090 (~124 vs ~81 tok/s).
Model A · Meta
Llama 3.1 8B Instruct8.0B · 128K context · Llama 3.1 Community · Jul 2024
Model B · Mistral AI
Mistral Nemo Instruct 240712.2B · 128K context · Apache 2.0 · Jul 2024
Choose Llama 3.1 8B Instruct if you want…
Fits an 8 GB GPU
Q4_K_M · 7.9 GB; Mistral Nemo Instruct 2407 needs 7 GB at its smallest quant
1.5× faster on RTX 4090
~124 vs ~81 tok/s
Lighter on memory
5.3 vs 8.1 GB at Q4_K_M
Choose Mistral Nemo Instruct 2407 if you want…
Higher llmrun Score
65.4 vs 62.5, ranges overlap
More permissive license
Apache 2.0 vs Llama 3.1 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
Llama 3.1 8B Instruct
Q4_K_M · ~33 tok/s
7.9 GB · up to 16Kmore headroom
Mistral Nemo Instruct 2407
IQ2_M · ~37 tok/s
7.8 GB · up to 16K
12 GB
RTX 3060 12GB · 12 GB tier
Llama 3.1 8B Instruct
Q4_K_M · ~44 tok/s
7.9 GB · up to 32Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~29 tok/s
11 GB · up to 16K
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Llama 3.1 8B Instruct
Q4_K_M · ~55 tok/s
7.9 GB · up to 32Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~36 tok/s
11 GB · up to 32K
24 GBreference
RTX 4090 · 24 GB tier
Llama 3.1 8B Instruct
Q4_K_M · ~124 tok/s
7.9 GB · up to 64Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~81 tok/s
11 GB · up to 64K
32 GB
RTX 5090 · 32 GB tier
Llama 3.1 8B Instruct
Q4_K_M · ~220 tok/s
7.9 GB · up to 128Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~144 tok/s
11 GB · up to 64K
48 GB
RTX A6000 · 48 GB tier
Llama 3.1 8B Instruct
Q4_K_M · ~94 tok/s
7.9 GB · up to 128Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~62 tok/s
11 GB · up to 128K
Mac 32 GB
Mac Mini M4 · Macs
Llama 3.1 8B Instruct
Q4_K_M · ~16 tok/s
7.9 GB · up to 128Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~10 tok/s
11 GB · up to 64K
Mac 64 GB
Mac Studio M4 Max · Macs
Llama 3.1 8B Instruct
Q4_K_M · ~72 tok/s
7.9 GB · up to 128Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~47 tok/s
11 GB · up to 128K
Mac 128 GB
Mac Studio M4 Max · Macs
Llama 3.1 8B Instruct
Q4_K_M · ~72 tok/s
7.9 GB · up to 128Kfaster
Mistral Nemo Instruct 2407
Q4_K_M · ~47 tok/s
11 GB · up to 128K
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Llama 3.1 8B Instruct
Mistral Nemo Instruct 2407
Coding
Llama 3.1 8B Instruct
Mistral Nemo Instruct 2407
no data
Science
Llama 3.1 8B Instruct
Mistral Nemo Instruct 2407
no data
Reasoning
Llama 3.1 8B Instruct
Mistral Nemo Instruct 2407
no data
Llama 3.1 8B Instruct · #88 of 92 open models · #31 of 34 that fit 24 GB
Mistral Nemo Instruct 2407 · #84 of 92 open models · #27 of 34 that fit 24 GB
Benchmarks
4 shared boards: Llama 3.1 8B Instruct leads 2, Mistral Nemo Instruct 2407 leads 2 · Benchmarks imported Oct 2026
Llama 3.1 8B Instruct
27.0%#86/97 open
IndependentEpoch AI · Jul 2024
Mistral Nemo Instruct 2407
29.9%#81/97 open
IndependentEpoch AI · Jul 2024
Llama 3.1 8B Instruct
44.3%#87/144 open
IndependentTIGER-Lab
Mistral Nemo Instruct 2407
44.8%#86/144 open
IndependentTIGER-Lab
Llama 3.1 8B Instruct
22.9%#28/39 open
IndependentEpoch AI · Jul 2024
Mistral Nemo Instruct 2407
10.8%#33/39 open
IndependentEpoch AI · Jul 2024
Llama 3.1 8B Instruct
50.9%#59/68 open
Lab-reportedEpoch AI · Jul 2024
Mistral Nemo Instruct 2407
48.6%#63/68 open
Lab-reportedEpoch AI · Jul 2024
12 more boards (other shared and single-model boards)
Llama 3.1 8B Instruct
15.1%#9/15 open
IndependentEpoch AI · Jul 2024
Mistral Nemo Instruct 2407
17.6%#6/15 open
IndependentEpoch AI · Jul 2024
Only Llama 3.1 8B Instruct (11)
- LMArena Text1211.3
- AIME 2024/20251.7%
- SciCode13.2%
- MMLU56.1%
- WeirdML1.7%
- Chess Puzzles0.0%
- CritPt0.0%
- LMCA5.4%
- GSM8K82.4%
- PIQA81.2%
- BoolQ82.8%
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
Llama 3.1 8B Instruct
3.8 GB3.2 GB file
32K 9.3 GB · 128K 26.9 GB
Mistral Nemo Instruct 2407
5.9 GB4.8 GB file
32K 12.2 GB · 128K 32.3 GB
Q3_K_S
Llama 3.1 8B Instruct
3.9 GB3.7 GB file
32K 9.4 GB · 128K 27.0 GB
Mistral Nemo Instruct 2407
6.1 GB5.5 GB file
32K 12.4 GB · 128K 32.5 GB
Q3_K_M
Llama 3.1 8B Instruct
4.3 GB4.0 GB file
32K 9.8 GB · 128K 27.4 GB
Mistral Nemo Instruct 2407
6.7 GB6.1 GB file
32K 13.0 GB · 128K 33.1 GB
Q4_0
Llama 3.1 8B Instruct
4.4 GB4.7 GB file
32K 9.9 GB · 128K 27.5 GB
Mistral Nemo Instruct 2407
6.8 GB7.1 GB file
32K 13.1 GB · 128K 33.3 GB
Q4_K_M
Llama 3.1 8B Instruct
5.3 GB4.9 GB file
32K 10.8 GB · 128K 28.4 GB
Mistral Nemo Instruct 2407
8.1 GB7.5 GB file
32K 14.4 GB · 128K 34.5 GB
Q5_K_M
Llama 3.1 8B Instruct
6.3 GB5.7 GB file
32K 11.8 GB · 128K 29.4 GB
Mistral Nemo Instruct 2407
9.5 GB8.7 GB file
32K 15.7 GB · 128K 35.9 GB
Q6_K
Llama 3.1 8B Instruct
7.3 GB6.6 GB file
32K 12.8 GB · 128K 30.4 GB
Mistral Nemo Instruct 2407
10.8 GB10.1 GB file
32K 17.1 GB · 128K 37.2 GB
Q8_0
Llama 3.1 8B Instruct
8.8 GB8.5 GB file
32K 14.3 GB · 128K 32.0 GB
Mistral Nemo Instruct 2407
13.0 GB13.0 GB file
32K 19.3 GB · 128K 39.4 GB
20 more quants
IQ2_XXS
Llama 3.1 8B Instruct
2.4 GB2.5 GB file
32K 7.9 GB · 128K 25.6 GB
Mistral Nemo Instruct 2407
4.1 GB3.6 GB file
32K 10.4 GB · 128K 30.5 GB
IQ2_XS
Llama 3.1 8B Instruct
2.7 GB2.6 GB file
32K 8.2 GB · 128K 25.8 GB
Mistral Nemo Instruct 2407
4.4 GB3.9 GB file
32K 10.7 GB · 128K 30.8 GB
IQ2_S
Llama 3.1 8B Instruct
2.8 GB2.8 GB file
32K 8.3 GB · 128K 25.9 GB
Mistral Nemo Instruct 2407
4.6 GB4.1 GB file
32K 10.8 GB · 128K 31.0 GB
IQ2_M
Llama 3.1 8B Instruct
3.0 GB2.9 GB file
32K 8.5 GB · 128K 26.1 GB
Mistral Nemo Instruct 2407
4.9 GB4.4 GB file
32K 11.1 GB · 128K 31.3 GB
IQ3_XXS
Llama 3.1 8B Instruct
3.4 GB3.3 GB file
32K 8.9 GB · 128K 26.5 GB
Mistral Nemo Instruct 2407
5.5 GB4.9 GB file
32K 11.8 GB · 128K 31.9 GB
Q2_K_S
Llama 3.1 8B Instruct
3.5 GB3.0 GB file
32K 9.0 GB · 128K 26.7 GB
Mistral Nemo Instruct 2407
not listed
IQ3_XS
Llama 3.1 8B Instruct
3.6 GB3.5 GB file
32K 9.1 GB · 128K 26.8 GB
Mistral Nemo Instruct 2407
5.8 GB5.3 GB file
32K 12.1 GB · 128K 32.2 GB
IQ3_S
Llama 3.1 8B Instruct
3.8 GB3.7 GB file
32K 9.3 GB · 128K 26.9 GB
Mistral Nemo Instruct 2407
5.9 GB5.6 GB file
32K 12.2 GB · 128K 32.3 GB
IQ3_M
Llama 3.1 8B Instruct
4.0 GB3.8 GB file
32K 9.5 GB · 128K 27.1 GB
Mistral Nemo Instruct 2407
6.2 GB5.7 GB file
32K 12.5 GB · 128K 32.7 GB
Q3_K_L
Llama 3.1 8B Instruct
4.5 GB4.3 GB file
32K 10.0 GB · 128K 27.7 GB
Mistral Nemo Instruct 2407
7.0 GB6.6 GB file
32K 13.3 GB · 128K 33.4 GB
IQ4_XS
Llama 3.1 8B Instruct
4.8 GB4.4 GB file
32K 10.3 GB · 128K 27.9 GB
Mistral Nemo Instruct 2407
7.3 GB6.7 GB file
32K 13.6 GB · 128K 33.7 GB
IQ4_NL
Llama 3.1 8B Instruct
5.0 GB4.7 GB file
32K 10.5 GB · 128K 28.1 GB
Mistral Nemo Instruct 2407
not listed
Q4_1
Llama 3.1 8B Instruct
5.0 GB5.1 GB file
32K 10.5 GB · 128K 28.1 GB
Mistral Nemo Instruct 2407
not listed
Q4_K_S
Llama 3.1 8B Instruct
5.0 GB4.7 GB file
32K 10.5 GB · 128K 28.1 GB
Mistral Nemo Instruct 2407
7.6 GB7.1 GB file
32K 13.9 GB · 128K 34.0 GB
Q4_K_L
Llama 3.1 8B Instruct
5.4 GB5.3 GB file
32K 10.9 GB · 128K 28.5 GB
Mistral Nemo Instruct 2407
8.2 GB8.0 GB file
32K 14.5 GB · 128K 34.6 GB
Q5_0
Llama 3.1 8B Instruct
5.5 GB5.6 GB file
32K 11.0 GB · 128K 28.6 GB
Mistral Nemo Instruct 2407
8.4 GB8.5 GB file
32K 14.7 GB · 128K 34.8 GB
Q5_1
Llama 3.1 8B Instruct
6.1 GB6.1 GB file
32K 11.6 GB · 128K 29.2 GB
Mistral Nemo Instruct 2407
not listed
Q5_K_S
Llama 3.1 8B Instruct
6.1 GB5.6 GB file
32K 11.6 GB · 128K 29.2 GB
Mistral Nemo Instruct 2407
9.1 GB8.5 GB file
32K 15.4 GB · 128K 35.6 GB
Q5_K_L
Llama 3.1 8B Instruct
6.4 GB6.1 GB file
32K 11.9 GB · 128K 29.5 GB
Mistral Nemo Instruct 2407
9.6 GB9.1 GB file
32K 15.9 GB · 128K 36.0 GB
BF16
Llama 3.1 8B Instruct
17.7 GB16.1 GB file
32K 23.2 GB · 128K 40.8 GB
Mistral Nemo Instruct 2407
25.2 GB~24.5 GB file
32K 31.5 GB · 128K 51.6 GB
Llama 3.1 8B Instruct
Ollama · Q4_K_M
ollama run hf.co/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_MMistral Nemo Instruct 2407
Ollama · Q4_K_M
ollama run hf.co/MaziyarPanahi/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M| Spec | Llama 3.1 8B Instruct | Mistral Nemo Instruct 2407 |
|---|---|---|
| Publisher | Meta | Mistral AI |
| Parameters | 8.0B | 12.2B |
| Architecture | — | MistralForCausalLM |
| Context | 128K tokens | 128K tokens |
| Modalities | Chat, Function-calling | Chat, Function-calling |
| License | Llama 3.1 Community | Apache 2.0 |
| Released | Jul 2024 | Jul 2024 |
Frequently Asked Questions
Which is better, Llama 3.1 8B Instruct or Mistral Nemo Instruct 2407?
Mistral Nemo Instruct 2407 leads llmrun Score 65.4 to 62.5 (ranges overlap); both fit 24 GB at Q4_K_M; Llama 3.1 8B Instruct is 1.5× faster on RTX 4090 (~124 vs ~81 tok/s). Choose Llama 3.1 8B Instruct for fits an 8 GB GPU and 1.5× faster on RTX 4090; choose Mistral Nemo Instruct 2407 for higher llmrun Score and more permissive license.
Which needs less VRAM, Llama 3.1 8B Instruct or Mistral Nemo Instruct 2407?
At Q4_K_M, Llama 3.1 8B Instruct requires 5.3 GB while Mistral Nemo Instruct 2407 needs 8.1 GB, making Llama 3.1 8B 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 Llama 3.1 8B Instruct (Q4_K_M) and 81 tok/s for Mistral Nemo Instruct 2407 (Q4_K_M), so Llama 3.1 8B Instruct is faster. Estimates, ±20%.
Can I run Llama 3.1 8B Instruct or Mistral Nemo Instruct 2407 on a 16 GB GPU?
Llama 3.1 8B Instruct fits at Q4_K_M; Mistral Nemo Instruct 2407 fits at Q4_K_M.
Which has a longer context window, Llama 3.1 8B Instruct or Mistral Nemo Instruct 2407?
Llama 3.1 8B Instruct supports 131,072 tokens and Mistral Nemo Instruct 2407 supports 131,072 tokens.