Gemma 2 9B IT vs Qwen2.5 7B Instruct
Gemma 2 9B IT leads llmrun Score 68.0 to 65.1 (ranges overlap); both fit 24 GB at Q4_K_M.
Model B · Alibaba
Qwen2.5 7B Instruct7.6B · 32K context · Apache 2.0 · Sep 2024
Choose Gemma 2 9B IT if you want…
Higher llmrun Score
68.0 vs 65.1, ranges overlap
Choose Qwen2.5 7B Instruct if you want…
Lighter on memory
5.0 vs 6.1 GB at Q4_K_M
Longer context window
32K vs 8K tokens
Also does function-calling
Gemma 2 9B IT doesn't list it
More permissive license
Apache 2.0 vs Gemma Terms
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
Gemma 2 9B IT
Q4_K_M · ~29 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~35 tok/s
5.8 GB · up to 32Kfaster
12 GB
RTX 3060 12GB · 12 GB tier
Gemma 2 9B IT
Q4_K_M · ~38 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~47 tok/s
5.8 GB · up to 32Kfaster
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Gemma 2 9B IT
Q4_K_M · ~48 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~58 tok/s
5.8 GB · up to 32Kfaster
24 GBreference
RTX 4090 · 24 GB tier
Gemma 2 9B IT
Q4_K_M · ~107 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~131 tok/s
5.8 GB · up to 32Kfaster
32 GB
RTX 5090 · 32 GB tier
Gemma 2 9B IT
Q4_K_M · ~191 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~233 tok/s
5.8 GB · up to 32Kfaster
48 GB
RTX A6000 · 48 GB tier
Gemma 2 9B IT
Q4_K_M · ~82 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~100 tok/s
5.8 GB · up to 32Kfaster
Mac 32 GB
Mac Mini M4 · Macs
Gemma 2 9B IT
Q4_K_M · ~14 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~17 tok/s
5.8 GB · up to 32Kfaster
Mac 64 GB
Mac Studio M4 Max · Macs
Gemma 2 9B IT
Q4_K_M · ~63 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~77 tok/s
5.8 GB · up to 32Kfaster
Mac 128 GB
Mac Studio M4 Max · Macs
Gemma 2 9B IT
Q4_K_M · ~63 tok/s
7.3 GB · up to 8K
Qwen2.5 7B Instruct
Q4_K_M · ~77 tok/s
5.8 GB · up to 32Kfaster
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Gemma 2 9B IT
Qwen2.5 7B Instruct
Reasoning
Gemma 2 9B IT
no data
Qwen2.5 7B Instruct
Gemma 2 9B IT · #93 of 100 open models · #29 of 35 that fit 24 GB
Qwen2.5 7B Instruct · #95 of 100 open models · #32 of 35 that fit 24 GB
Benchmarks
2 shared boards: Gemma 2 9B IT leads 0, Qwen2.5 7B Instruct leads 2 · Benchmarks imported Oct 2026
Gemma 2 9B IT
27.5%#86/98 open
IndependentEpoch AI · Jun 2024
Qwen2.5 7B Instruct
35.5%#75/98 open
IndependentEpoch AI · Sep 2024
Gemma 2 9B IT
0.6%#82/86 open
IndependentEpoch AI · Jun 2024
Qwen2.5 7B Instruct
2.5%#75/86 open
IndependentEpoch AI · Sep 2024
7 more boards (other shared and single-model boards)
Gemma 2 9B IT
72.1%#25/85 open
Lab-reportedEpoch AI · Jun 2024
Qwen2.5 7B Instruct
72.9%#24/85 open
Lab-reportedEpoch AI · Sep 2024
Only Gemma 2 9B IT (3)
- LMArena Text1267.0
- MMLU-Pro52.1%
- MATH Level 521.0%
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
Gemma 2 9B IT
4.3 GB3.8 GB file
32K — · 128K —
Qwen2.5 7B Instruct
3.7 GB3.0 GB file
32K 5.4 GB · 128K —
Q3_K_S
Gemma 2 9B IT
4.5 GB4.3 GB file
32K — · 128K —
Qwen2.5 7B Instruct
3.8 GB3.5 GB file
32K 5.5 GB · 128K —
Q3_K_M
Gemma 2 9B IT
5.0 GB4.8 GB file
32K — · 128K —
Qwen2.5 7B Instruct
4.1 GB3.8 GB file
32K 5.9 GB · 128K —
Q4_0
Gemma 2 9B IT
5.1 GB5.4 GB file
32K — · 128K —
Qwen2.5 7B Instruct
4.2 GB4.4 GB file
32K 6.0 GB · 128K —
Q4_K_M
Gemma 2 9B IT
6.1 GB5.8 GB file
32K — · 128K —
Qwen2.5 7B Instruct
5.0 GB4.7 GB file
32K 6.8 GB · 128K —
Q5_K_M
Gemma 2 9B IT
7.2 GB6.6 GB file
32K — · 128K —
Qwen2.5 7B Instruct
5.8 GB5.4 GB file
32K 7.6 GB · 128K —
Q6_K
Gemma 2 9B IT
8.4 GB7.6 GB file
32K — · 128K —
Qwen2.5 7B Instruct
6.7 GB6.3 GB file
32K 8.5 GB · 128K —
Q8_0
Gemma 2 9B IT
10.2 GB9.8 GB file
32K — · 128K —
Qwen2.5 7B Instruct
8.0 GB8.1 GB file
32K 9.8 GB · 128K —
20 more quants
IQ2_XXS
Gemma 2 9B IT
2.8 GB2.8 GB file
32K — · 128K —
Qwen2.5 7B Instruct
2.5 GB2.3 GB file
32K 4.3 GB · 128K —
IQ2_XS
Gemma 2 9B IT
3.1 GB3.1 GB file
32K — · 128K —
Qwen2.5 7B Instruct
2.7 GB2.5 GB file
32K 4.5 GB · 128K —
IQ2_S
Gemma 2 9B IT
3.2 GB3.2 GB file
32K — · 128K —
Qwen2.5 7B Instruct
2.8 GB2.6 GB file
32K 4.6 GB · 128K —
IQ2_M
Gemma 2 9B IT
3.4 GB3.4 GB file
32K — · 128K —
Qwen2.5 7B Instruct
3.0 GB2.8 GB file
32K 4.8 GB · 128K —
IQ3_XXS
Gemma 2 9B IT
3.9 GB3.8 GB file
32K — · 128K —
Qwen2.5 7B Instruct
3.4 GB3.1 GB file
32K 5.1 GB · 128K —
Q2_K_S
Gemma 2 9B IT
not listed
Qwen2.5 7B Instruct
3.5 GB2.8 GB file
32K 5.2 GB · 128K —
IQ3_XS
Gemma 2 9B IT
4.2 GB4.1 GB file
32K — · 128K —
Qwen2.5 7B Instruct
3.6 GB3.3 GB file
32K 5.3 GB · 128K —
IQ3_S
Gemma 2 9B IT
4.3 GB4.3 GB file
32K — · 128K —
Qwen2.5 7B Instruct
3.7 GB3.5 GB file
32K 5.4 GB · 128K —
IQ3_M
Gemma 2 9B IT
4.6 GB4.5 GB file
32K — · 128K —
Qwen2.5 7B Instruct
3.8 GB3.6 GB file
32K 5.6 GB · 128K —
Q3_K_L
Gemma 2 9B IT
5.2 GB5.1 GB file
32K — · 128K —
Qwen2.5 7B Instruct
4.3 GB4.1 GB file
32K 6.1 GB · 128K —
IQ4_XS
Gemma 2 9B IT
5.5 GB5.2 GB file
32K — · 128K —
Qwen2.5 7B Instruct
4.5 GB4.2 GB file
32K 6.3 GB · 128K —
IQ4_NL
Gemma 2 9B IT
not listed
Qwen2.5 7B Instruct
4.7 GB4.4 GB file
32K 6.5 GB · 128K —
Q4_1
Gemma 2 9B IT
5.7 GB6.0 GB file
32K — · 128K —
Qwen2.5 7B Instruct
4.7 GB4.9 GB file
32K 6.5 GB · 128K —
Q4_K_S
Gemma 2 9B IT
5.7 GB5.5 GB file
32K — · 128K —
Qwen2.5 7B Instruct
4.7 GB4.5 GB file
32K 6.5 GB · 128K —
Q4_K_L
Gemma 2 9B IT
6.2 GB6.0 GB file
32K — · 128K —
Qwen2.5 7B Instruct
5.1 GB5.1 GB file
32K 6.8 GB · 128K —
Q5_0
Gemma 2 9B IT
6.4 GB6.5 GB file
32K — · 128K —
Qwen2.5 7B Instruct
5.2 GB5.3 GB file
32K 6.9 GB · 128K —
Q5_1
Gemma 2 9B IT
7.0 GB7.0 GB file
32K — · 128K —
Qwen2.5 7B Instruct
5.7 GB5.8 GB file
32K 7.4 GB · 128K —
Q5_K_S
Gemma 2 9B IT
7.0 GB6.5 GB file
32K — · 128K —
Qwen2.5 7B Instruct
5.7 GB5.3 GB file
32K 7.4 GB · 128K —
Q5_K_L
Gemma 2 9B IT
7.4 GB6.9 GB file
32K — · 128K —
Qwen2.5 7B Instruct
5.9 GB5.8 GB file
32K 7.7 GB · 128K —
BF16
Gemma 2 9B IT
20.3 GB~18.5 GB file
32K — · 128K —
Qwen2.5 7B Instruct
15.7 GB~15.2 GB file
32K 17.4 GB · 128K —
Gemma 2 9B IT
Ollama · Q4_K_M
ollama run hf.co/bartowski/gemma-2-9b-it-GGUF:Q4_K_MQwen2.5 7B Instruct
Ollama · Q4_K_M
ollama run hf.co/bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M| Spec | Gemma 2 9B IT | Qwen2.5 7B Instruct |
|---|---|---|
| Publisher | Alibaba | |
| Parameters | 9.2B | 7.6B |
| Architecture | — | Qwen2ForCausalLM |
| Context | 8K tokens | 32K tokens |
| Modalities | Chat | Chat, Function-calling |
| License | Gemma Terms | Apache 2.0 |
| Released | Jun 2024 | Sep 2024 |
Frequently Asked Questions
Which is better, Gemma 2 9B IT or Qwen2.5 7B Instruct?
Gemma 2 9B IT leads llmrun Score 68.0 to 65.1 (ranges overlap); both fit 24 GB at Q4_K_M. Choose Gemma 2 9B IT for higher llmrun Score; choose Qwen2.5 7B Instruct for lighter on memory and longer context window.
Which needs less VRAM, Gemma 2 9B IT or Qwen2.5 7B Instruct?
At Q4_K_M, Gemma 2 9B IT requires 6.1 GB while Qwen2.5 7B Instruct needs 5.0 GB, making Qwen2.5 7B Instruct the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 107 tok/s for Gemma 2 9B IT (Q4_K_M) and 131 tok/s for Qwen2.5 7B Instruct (Q4_K_M), so Qwen2.5 7B Instruct is faster. Estimates, ±20%.
Can I run Gemma 2 9B IT or Qwen2.5 7B Instruct on a 16 GB GPU?
Gemma 2 9B IT fits at Q4_K_M; Qwen2.5 7B Instruct fits at Q4_K_M.
Which has a longer context window, Gemma 2 9B IT or Qwen2.5 7B Instruct?
Gemma 2 9B IT supports 8,192 tokens and Qwen2.5 7B Instruct supports 32,768 tokens.