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Gemma 2 9B Instruct vs Qwen 2.5 7B Instruct

Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.

Quick verdict

Qwen 2.5 7B Instruct is more hardware-efficient — it needs 4.8 GB at Q4_K_M vs 8.3 GB for Gemma 2 9B Instruct, fitting on 66 GPUs natively.

VRAM at each quantization (8k context)

QuantGemma 2 9B InstructQwen 2.5 7B InstructDiff
FP1623.8 GB17.6 GB+35%
Q813.5 GB9.0 GB+49%
Q6_K10.9 GB6.9 GB+58%
Q5_K_M9.6 GB5.8 GB+64%
Q4_K_M8.3 GB4.8 GB+74%
Q3_K_M7.3 GB3.9 GB+85%
Q2_K6.2 GB3.1 GB+103%

Diff is Gemma 2 9B Instruct relative to Qwen 2.5 7B Instruct. Green = lower VRAM (fits more GPUs).

Model specifications

SpecGemma 2 9B InstructQwen 2.5 7B Instruct
OrgGoogleAlibaba
Parameters9.2B7.6B
ArchitectureDenseDense
Context8k tokens125k tokens
Modalitiestexttext
LicenseGemmaApache 2.0
CommercialYesYes
Released2024-06-272024-09-19
GPUs (native)63 / 6766 / 67

Benchmark scores

BenchmarkGemma 2 9B InstructQwen 2.5 7B Instruct
MMLU-Pro32.036.5
GPQA31.536.4
IFEval74.475.5
MATH44.375.5
HumanEval60.484.8
Arena ELO1190.01200.0

Green = higher score (better). — = not yet available.

GPUs that run only Gemma 2 9B Instruct(0)

Every GPU that runs Gemma 2 9B Instruct also runs Qwen 2.5 7B Instruct.

GPUs that run only Qwen 2.5 7B Instruct(3)

GPUs that run both natively(63)

Which should you use?

Choose Gemma 2 9B Instruct if:
  • • You want maximum capability and have a 9 GB+ GPU
Choose Qwen 2.5 7B Instruct if:
  • • You have limited VRAM — it's a smaller model needing 4.8 GB vs 8.3 GB
  • • Long context matters — it supports 125k tokens vs 8k
  • • Benchmark quality matters — scores 36.5 vs 32.0 on MMLU-Pro

Frequently asked questions

Which is better, Gemma 2 9B Instruct or Qwen 2.5 7B Instruct?
Gemma 2 9B Instruct has 9.2B parameters vs 7.6B for Qwen 2.5 7B Instruct, so Gemma 2 9B Instruct is the larger model. Qwen 2.5 7B Instruct is more hardware-efficient, needing 4.8 GB at Q4_K_M vs 8.3 GB. Qwen 2.5 7B Instruct runs on more GPUs natively (66 vs 63). On MMLU-Pro, Qwen 2.5 7B Instruct scores higher (36.5 vs 32.0).
How much VRAM does Gemma 2 9B Instruct need vs Qwen 2.5 7B Instruct?
At Q4_K_M quantization with 8k context, Gemma 2 9B Instruct needs approximately 8.3 GB of VRAM, while Qwen 2.5 7B Instruct needs 4.8 GB. At FP16, Gemma 2 9B Instruct requires 23.8 GB vs 17.6 GB for Qwen 2.5 7B Instruct.
Can you run Gemma 2 9B Instruct on the same GPUs as Qwen 2.5 7B Instruct?
Yes, 63 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 4080. However, no GPU can run Gemma 2 9B Instruct without also fitting Qwen 2.5 7B Instruct, and 3 GPUs can run Qwen 2.5 7B Instruct but not Gemma 2 9B Instruct.
What is the difference between Gemma 2 9B Instruct and Qwen 2.5 7B Instruct?
Gemma 2 9B Instruct has 9.2B parameters (dense) with a 8k context window. Qwen 2.5 7B Instruct has 7.6B parameters (dense) with a 125k context window. Licensing differs: Gemma 2 9B Instruct is Gemma while Qwen 2.5 7B Instruct is Apache 2.0.
Which model fits in 24 GB of VRAM, Gemma 2 9B Instruct or Qwen 2.5 7B Instruct?
Both fit in 24 GB of VRAM at Q4_K_M — Gemma 2 9B Instruct needs 8.3 GB and Qwen 2.5 7B Instruct needs 4.8 GB.
Full Gemma 2 9B Instruct page →Full Qwen 2.5 7B Instruct page →Check your hardware →