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Mistral 7B vs Gemma 2 9B

Mistral
Mistral 7B

Mistral AI · 7.3B params · Quality: 56

Google
Gemma 2 9B

Google · 9.2B params · Quality: 68

Architecture Comparison

SpecMistral 7BGemma 2 9B
TypeDENSEDENSE
Total Parameters7.3B9.2B
Active Parameters7.3B9.2B
Layers3242
Hidden Dimension4,0963,584
Attention Heads3216
KV Heads88
Context Length32,7688,192
Precision (default)BF16BF16

Memory Requirements

PrecisionMistral 7BGemma 2 9B
BF16 Weights14.6 GB18.4 GB
FP8 Weights7.3 GB9.2 GB
INT4 Weights3.6 GB4.6 GB
KV-Cache / Token131072 B344064 B
Activation Estimate1.00 GB1.00 GB

Minimum GPUs Needed (BF16)

H100 SXM1 GPU1 GPU
L40S1 GPU1 GPU

Quality Benchmarks

BenchmarkMistral 7BGemma 2 9B
Overall5668
MMLU62.571.3
HumanEval32.040.0
GSM8K52.276.0
MT-Bench71.078.0

Mistral 7B

MMLU
62.5
HumanEval
32.0
GSM8K
52.2
MT-Bench
71.0

Gemma 2 9B

MMLU
71.3
HumanEval
40.0
GSM8K
76.0
MT-Bench
78.0

Capabilities

FeatureMistral 7BGemma 2 9B
Tool Use✗ No✗ No
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✗ No
Multilingual✓ Yes✓ Yes
Structured Output✗ No✓ Yes

API Pricing Comparison

Cheapest Output (Mistral 7B)

$0.07/M

Input: $0.07/M

Cheapest Output (Gemma 2 9B)

$0.10/M

Input: $0.10/M

ProviderMistral 7B In $/MOut $/MGemma 2 9B In $/MOut $/M
deepinfra$0.07$0.07$0.10$0.10
together$0.20$0.20$0.20$0.20

Recommendation Summary

  • Gemma 2 9B scores higher on overall quality (68 vs 56).
  • Mistral 7B is cheaper per output token ($0.07/M vs $0.10/M).
  • Mistral 7B has a smaller memory footprint (14.6 GB vs 18.4 GB BF16), making it easier to deploy on fewer GPUs.
  • Mistral 7B supports a longer context window (32,768 vs 8,192 tokens).
  • Gemma 2 9B is stronger at code generation (HumanEval: 40.0 vs 32.0).
  • Gemma 2 9B is better at math reasoning (GSM8K: 76.0 vs 52.2).

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