Qwen2.5 7B Instruct vs Qwen3.5 4B
Qwen3.5 4B leads llmrun Score 98.5 to 65.1; both fit 24 GB at Q4_K_M; Qwen3.5 4B is 1.5× faster on RTX 4090 (~201 vs ~131 tok/s).
Model A · Alibaba
Qwen2.5 7B Instruct7.6B · 32K context · Apache 2.0 · Sep 2024
Model B · Alibaba
Qwen3.5 4B4.7B · 256K context · Apache 2.0 · Feb 2026
Choose Qwen2.5 7B Instruct if you want…
Also does chat
Qwen3.5 4B doesn't list it
Choose Qwen3.5 4B if you want…
Higher llmrun Score
98.5 vs 65.1
1.5× faster on RTX 4090
~201 vs ~131 tok/s
Lighter on memory
3.3 vs 5.0 GB at Q4_K_M
Longer context window
256K vs 32K tokens
Also does vision
Qwen2.5 7B Instruct doesn't list it
Newer release
Feb 2026 vs Sep 2024
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
Qwen2.5 7B Instruct
Q4_K_M · ~35 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~54 tok/s
3.4 GB · up to 128Kfaster
12 GB
RTX 3060 12GB · 12 GB tier
Qwen2.5 7B Instruct
Q4_K_M · ~47 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~72 tok/s
3.4 GB · up to 256Kfaster
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Qwen2.5 7B Instruct
Q4_K_M · ~58 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~89 tok/s
3.4 GB · up to 256Kfaster
24 GBreference
RTX 4090 · 24 GB tier
Qwen2.5 7B Instruct
Q4_K_M · ~131 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~201 tok/s
3.4 GB · up to 256Kfaster
32 GB
RTX 5090 · 32 GB tier
Qwen2.5 7B Instruct
Q4_K_M · ~233 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~357 tok/s
3.4 GB · up to 256Kfaster
48 GB
RTX A6000 · 48 GB tier
Qwen2.5 7B Instruct
Q4_K_M · ~100 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~153 tok/s
3.4 GB · up to 256Kfaster
Mac 32 GB
Mac Mini M4 · Macs
Qwen2.5 7B Instruct
Q4_K_M · ~17 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~26 tok/s
3.4 GB · up to 256Kfaster
Mac 64 GB
Mac Studio M4 Max · Macs
Qwen2.5 7B Instruct
Q4_K_M · ~77 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~117 tok/s
3.4 GB · up to 256Kfaster
Mac 128 GB
Mac Studio M4 Max · Macs
Qwen2.5 7B Instruct
Q4_K_M · ~77 tok/s
5.8 GB · up to 32K
Qwen3.5 4B
Q4_K_M · ~117 tok/s
3.4 GB · up to 256Kfaster
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Qwen2.5 7B Instruct
Qwen3.5 4B
Reasoning
Qwen2.5 7B Instruct
Qwen3.5 4B
no data
Qwen2.5 7B Instruct · #102 of 106 open models · #33 of 36 that fit 24 GB
Qwen3.5 4B · #64 of 106 open models · #12 of 36 that fit 24 GB
Benchmarks
1 shared board: Qwen2.5 7B Instruct leads 0, Qwen3.5 4B leads 1 · Benchmarks imported Nov 2026
Qwen2.5 7B Instruct
2.5%#77/88 open
IndependentEpoch AI · Sep 2024
Qwen3.5 4B
55.8%#43/88 open
IndependentEpoch AI · Feb 2026
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
Qwen2.5 7B Instruct
3.7 GB3.0 GB file
32K 5.4 GB · 128K —
Qwen3.5 4B
2.5 GB2.2 GB file
32K 3.0 GB · 128K 5.0 GB
Q3_K_S
Qwen2.5 7B Instruct
3.8 GB3.5 GB file
32K 5.5 GB · 128K —
Qwen3.5 4B
2.5 GB2.1 GB file
32K 3.0 GB · 128K 5.0 GB
Q3_K_M
Qwen2.5 7B Instruct
4.1 GB3.8 GB file
32K 5.9 GB · 128K —
Qwen3.5 4B
2.7 GB2.3 GB file
32K 3.2 GB · 128K 5.3 GB
Q4_0
Qwen2.5 7B Instruct
4.2 GB4.4 GB file
32K 6.0 GB · 128K —
Qwen3.5 4B
2.8 GB2.6 GB file
32K 3.3 GB · 128K 5.3 GB
Q4_K_M
Qwen2.5 7B Instruct
5.0 GB4.7 GB file
32K 6.8 GB · 128K —
Qwen3.5 4B
3.3 GB2.7 GB file
32K 3.8 GB · 128K 5.8 GB
Q5_K_M
Qwen2.5 7B Instruct
5.8 GB5.4 GB file
32K 7.6 GB · 128K —
Qwen3.5 4B
3.8 GB3.1 GB file
32K 4.3 GB · 128K 6.3 GB
Q6_K
Qwen2.5 7B Instruct
6.7 GB6.3 GB file
32K 8.5 GB · 128K —
Qwen3.5 4B
4.3 GB3.5 GB file
32K 4.8 GB · 128K 6.8 GB
Q8_0
Qwen2.5 7B Instruct
8.0 GB8.1 GB file
32K 9.8 GB · 128K —
Qwen3.5 4B
5.1 GB4.5 GB file
32K 5.6 GB · 128K 7.7 GB
20 more quants
IQ2_XXS
Qwen2.5 7B Instruct
2.5 GB2.3 GB file
32K 4.3 GB · 128K —
Qwen3.5 4B
1.8 GB1.5 GB file
32K 2.3 GB · 128K 4.3 GB
IQ2_XS
Qwen2.5 7B Instruct
2.7 GB2.5 GB file
32K 4.5 GB · 128K —
Qwen3.5 4B
not listed
IQ2_S
Qwen2.5 7B Instruct
2.8 GB2.6 GB file
32K 4.6 GB · 128K —
Qwen3.5 4B
not listed
IQ2_M
Qwen2.5 7B Instruct
3.0 GB2.8 GB file
32K 4.8 GB · 128K —
Qwen3.5 4B
2.0 GB1.8 GB file
32K 2.5 GB · 128K 4.6 GB
IQ3_XXS
Qwen2.5 7B Instruct
3.4 GB3.1 GB file
32K 5.1 GB · 128K —
Qwen3.5 4B
2.3 GB1.9 GB file
32K 2.8 GB · 128K 4.8 GB
Q2_K_S
Qwen2.5 7B Instruct
3.5 GB2.8 GB file
32K 5.2 GB · 128K —
Qwen3.5 4B
not listed
IQ3_XS
Qwen2.5 7B Instruct
3.6 GB3.3 GB file
32K 5.3 GB · 128K —
Qwen3.5 4B
2.4 GB2.4 GB file
32K 2.9 GB · 128K 4.9 GB
IQ3_S
Qwen2.5 7B Instruct
3.7 GB3.5 GB file
32K 5.4 GB · 128K —
Qwen3.5 4B
not listed
IQ3_M
Qwen2.5 7B Instruct
3.8 GB3.6 GB file
32K 5.6 GB · 128K —
Qwen3.5 4B
2.6 GB2.5 GB file
32K 3.1 GB · 128K 5.1 GB
Q3_K_L
Qwen2.5 7B Instruct
4.3 GB4.1 GB file
32K 6.1 GB · 128K —
Qwen3.5 4B
2.9 GB2.7 GB file
32K 3.4 GB · 128K 5.4 GB
IQ4_XS
Qwen2.5 7B Instruct
4.5 GB4.2 GB file
32K 6.3 GB · 128K —
Qwen3.5 4B
3.0 GB2.5 GB file
32K 3.5 GB · 128K 5.5 GB
IQ4_NL
Qwen2.5 7B Instruct
4.7 GB4.5 GB file
32K 6.5 GB · 128K —
Qwen3.5 4B
3.1 GB2.6 GB file
32K 3.6 GB · 128K 5.6 GB
Q4_1
Qwen2.5 7B Instruct
4.7 GB4.9 GB file
32K 6.5 GB · 128K —
Qwen3.5 4B
3.1 GB2.8 GB file
32K 3.6 GB · 128K 5.6 GB
Q4_K_S
Qwen2.5 7B Instruct
4.7 GB4.5 GB file
32K 6.5 GB · 128K —
Qwen3.5 4B
3.1 GB2.6 GB file
32K 3.6 GB · 128K 5.6 GB
Q4_K_L
Qwen2.5 7B Instruct
5.1 GB5.1 GB file
32K 6.8 GB · 128K —
Qwen3.5 4B
3.3 GB3.2 GB file
32K 3.8 GB · 128K 5.8 GB
Q5_0
Qwen2.5 7B Instruct
5.2 GB5.3 GB file
32K 6.9 GB · 128K —
Qwen3.5 4B
not listed
Q5_1
Qwen2.5 7B Instruct
5.7 GB5.8 GB file
32K 7.4 GB · 128K —
Qwen3.5 4B
not listed
Q5_K_S
Qwen2.5 7B Instruct
5.7 GB5.3 GB file
32K 7.4 GB · 128K —
Qwen3.5 4B
3.7 GB3.0 GB file
32K 4.2 GB · 128K 6.2 GB
Q5_K_L
Qwen2.5 7B Instruct
5.9 GB5.8 GB file
32K 7.7 GB · 128K —
Qwen3.5 4B
3.9 GB3.6 GB file
32K 4.4 GB · 128K 6.4 GB
BF16
Qwen2.5 7B Instruct
15.7 GB~15.2 GB file
32K 17.4 GB · 128K —
Qwen3.5 4B
9.8 GB8.4 GB file
32K 10.3 GB · 128K 12.3 GB
Qwen2.5 7B Instruct
Ollama · Q4_K_M
ollama run hf.co/Qwen/Qwen2.5-7B-Instruct-GGUF:Q4_K_MQwen3.5 4B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.5-4B-GGUF:Q4_K_M| Spec | Qwen2.5 7B Instruct | Qwen3.5 4B |
|---|---|---|
| Publisher | Alibaba | Alibaba |
| Parameters | 7.6B | 4.7B |
| Architecture | Qwen2ForCausalLM | Qwen3_5ForConditionalGeneration |
| Context | 32K tokens | 256K tokens |
| Modalities | Chat, Function-calling | Vision, Function-calling |
| License | Apache 2.0 | Apache 2.0 |
| Released | Sep 2024 | Feb 2026 |
Frequently Asked Questions
Which is better, Qwen2.5 7B Instruct or Qwen3.5 4B?
Qwen3.5 4B leads llmrun Score 98.5 to 65.1; both fit 24 GB at Q4_K_M; Qwen3.5 4B is 1.5× faster on RTX 4090 (~201 vs ~131 tok/s). Choose Qwen2.5 7B Instruct for also does chat; choose Qwen3.5 4B for higher llmrun Score and 1.5× faster on RTX 4090.
Which needs less VRAM, Qwen2.5 7B Instruct or Qwen3.5 4B?
At Q4_K_M, Qwen2.5 7B Instruct requires 5.0 GB while Qwen3.5 4B needs 3.3 GB, making Qwen3.5 4B the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 131 tok/s for Qwen2.5 7B Instruct (Q4_K_M) and 201 tok/s for Qwen3.5 4B (Q4_K_M), so Qwen3.5 4B is faster. Estimates, ±20%.
Can I run Qwen2.5 7B Instruct or Qwen3.5 4B on a 16 GB GPU?
Qwen2.5 7B Instruct fits at Q4_K_M; Qwen3.5 4B fits at Q4_K_M.
Which has a longer context window, Qwen2.5 7B Instruct or Qwen3.5 4B?
Qwen2.5 7B Instruct supports 32,768 tokens and Qwen3.5 4B supports 262,144 tokens.