Llama 3.1 70B vs Mistral Large 2
Architecture Comparison
SpecLlama 3.1 70BMistral Large 2
TypeDENSEDENSE
Total Parameters70.6B123B
Active Parameters70.6B123B
Layers8088
Hidden Dimension8,19212,288
Attention Heads6496
KV Heads88
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionLlama 3.1 70BMistral Large 2
BF16 Weights141.2 GB246.0 GB
FP8 Weights70.6 GB123.0 GB
INT4 Weights35.3 GB61.5 GB
KV-Cache / Token327680 B360448 B
Activation Estimate2.50 GB3.50 GB
Minimum GPUs Needed (BF16)
H100 SXM3 GPUs4 GPUs
L40S4 GPUs7 GPUs
Quality Benchmarks
BenchmarkLlama 3.1 70BMistral Large 2
Overall8282
MMLU83.684.0
HumanEval58.553.0
GSM8K93.091.2
MT-Bench85.084.0
Llama 3.1 70B
MMLU
83.6
HumanEval
58.5
GSM8K
93.0
MT-Bench
85.0
Mistral Large 2
MMLU
84.0
HumanEval
53.0
GSM8K
91.2
MT-Bench
84.0
Capabilities
FeatureLlama 3.1 70BMistral Large 2
Tool Use✓ Yes✓ Yes
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✗ No
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (Llama 3.1 70B)
$0.79/M
Input: $0.59/M
Cheapest Output (Mistral Large 2)
$2.50/M
Input: $2.50/M
| Provider | Llama 3.1 70B In $/M | Out $/M | Mistral Large 2 In $/M | Out $/M |
|---|---|---|---|---|
| groq | $0.59 | $0.79 | — | — |
| together | $0.88 | $0.88 | $2.50 | $2.50 |
| fireworks | $0.90 | $0.90 | — | — |
| mistral | — | — | $2.00 | $6.00 |
Recommendation Summary
- ‣Llama 3.1 70B is cheaper per output token ($0.79/M vs $2.50/M).
- ‣Llama 3.1 70B has a smaller memory footprint (141.2 GB vs 246.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.1 70B is stronger at code generation (HumanEval: 58.5 vs 53.0).
- ‣Llama 3.1 70B is better at math reasoning (GSM8K: 93.0 vs 91.2).