Skip to content

Llama 3.3 70B vs Mistral Large 2

Meta
Llama 3.3 70B

Meta · 70.6B params · Quality: 84

Mistral
Mistral Large 2

Mistral AI · 123B params · Quality: 82

Architecture Comparison

SpecLlama 3.3 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 3.3 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 3.3 70BMistral Large 2
Overall8482
MMLU86.084.0
HumanEval60.053.0
GSM8K94.091.2
MT-Bench86.084.0

Llama 3.3 70B

MMLU
86.0
HumanEval
60.0
GSM8K
94.0
MT-Bench
86.0

Mistral Large 2

MMLU
84.0
HumanEval
53.0
GSM8K
91.2
MT-Bench
84.0

Capabilities

FeatureLlama 3.3 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 3.3 70B)

$0.79/M

Input: $0.59/M

Cheapest Output (Mistral Large 2)

$2.50/M

Input: $2.50/M

ProviderLlama 3.3 70B In $/MOut $/MMistral Large 2 In $/MOut $/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 3.3 70B scores higher on overall quality (84 vs 82).
  • Llama 3.3 70B is cheaper per output token ($0.79/M vs $2.50/M).
  • Llama 3.3 70B has a smaller memory footprint (141.2 GB vs 246.0 GB BF16), making it easier to deploy on fewer GPUs.
  • Llama 3.3 70B is stronger at code generation (HumanEval: 60.0 vs 53.0).
  • Llama 3.3 70B is better at math reasoning (GSM8K: 94.0 vs 91.2).

Compare Other Models