Qwen2.5 7B Instruct vs Qwen3.5 9B

Qwen3.5 9B leads llmrun Score 99.4 to 65.1; both fit 24 GB at Q4_K_M; Qwen2.5 7B Instruct is 1.3× faster on RTX 4090 (~131 vs ~103 tok/s).

Model A · Alibaba

Qwen2.5 7B Instruct

65.1llmrun Score

7.6B · 32K context · Apache 2.0 · Sep 2024

ChatFunctions

Model B · Alibaba

Qwen3.5 9B

99.4llmrun Score

9.7B · 256K context · Apache 2.0 · Feb 2026

VisionFunctions

Which should you choose?

Choose Qwen2.5 7B Instruct if you want…

1.3× faster on RTX 4090
~131 vs ~103 tok/s
Lighter on memory
5.0 vs 6.4 GB at Q4_K_M
Also does chat
Qwen3.5 9B doesn't list it

Choose Qwen3.5 9B if you want…

Higher llmrun Score
99.4 vs 65.1
Stronger at reasoning
97.0 vs 65.5
Ahead on the benchmarks
4 of 4 shared boards
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%.

MemoryQwen2.5 7B InstructQwen3.5 9B

8 GB

RTX 4060 · 8 GB tier

Qwen2.5 7B Instruct

Q4_K_M · ~35 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~28 tok/s

6.6 GB · up to 32K

12 GB

RTX 3060 12GB · 12 GB tier

Qwen2.5 7B Instruct

Q4_K_M · ~47 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~37 tok/s

6.6 GB · up to 128K

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Qwen2.5 7B Instruct

Q4_K_M · ~58 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~46 tok/s

6.6 GB · up to 256K

24 GBreference

RTX 4090 · 24 GB tier

Qwen2.5 7B Instruct

Q4_K_M · ~131 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~103 tok/s

6.6 GB · up to 256K

32 GB

RTX 5090 · 32 GB tier

Qwen2.5 7B Instruct

Q4_K_M · ~233 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~183 tok/s

6.6 GB · up to 256K

48 GB

RTX A6000 · 48 GB tier

Qwen2.5 7B Instruct

Q4_K_M · ~100 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~79 tok/s

6.6 GB · up to 256K

Mac 32 GB

Mac Mini M4 · Macs

Qwen2.5 7B Instruct

Q4_K_M · ~17 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~13 tok/s

6.6 GB · up to 256K

Mac 64 GB

Mac Studio M4 Max · Macs

Qwen2.5 7B Instruct

Q4_K_M · ~77 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~60 tok/s

6.6 GB · up to 256K

Mac 128 GB

Mac Studio M4 Max · Macs

Qwen2.5 7B Instruct

Q4_K_M · ~77 tok/s

5.8 GB · up to 32Kfaster

Qwen3.5 9B

Q4_K_M · ~60 tok/s

6.6 GB · up to 256K

Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).

llmrun Score

with its 90% range · bars share one scale

Qwen2.5 7B Instruct Qwen3.5 9B

Overall

Qwen2.5 7B Instruct

65.155–76

Qwen3.5 9B

99.496–103

Science

Qwen2.5 7B Instruct

no data

Qwen3.5 9B

104.596–113

Reasoning

Qwen2.5 7B Instruct

65.550–81

Qwen3.5 9B

97.089–106

Qwen2.5 7B Instruct · #102 of 106 open models · #33 of 36 that fit 24 GB

Qwen3.5 9B · #59 of 106 open models · #10 of 36 that fit 24 GB

Benchmarks

4 shared boards: Qwen2.5 7B Instruct leads 0, Qwen3.5 9B leads 4 · Benchmarks imported Nov 2026

BoardQwen2.5 7B InstructQwen3.5 9B

GPQA Diamond

Qwen2.5 7B Instruct

35.5%#77/100 open

IndependentEpoch AI · Sep 2024

Qwen3.5 9B

79.0%#28/100 open

IndependentEpoch AI · Feb 2026

AIME 2024/2025

Qwen2.5 7B Instruct

2.5%#77/88 open

IndependentEpoch AI · Sep 2024

Qwen3.5 9B

61.7%#39/88 open

IndependentEpoch AI · Feb 2026

DTBench

Qwen2.5 7B Instruct

47.7%#66/70 open

Lab-reportedEpoch AI · Sep 2024

Qwen3.5 9B

71.2%#33/70 open

Lab-reportedEpoch AI · Feb 2026

LMCA

Qwen2.5 7B Instruct

6.4%#52/56 open

Lab-reportedEpoch AI · Sep 2024

Qwen3.5 9B

24.5%#30/56 open

Lab-reportedEpoch AI · Feb 2026

6 more boards (other shared and single-model boards)

Only Qwen2.5 7B Instruct (2)

MMLU72.9%
BALROG7.8%

Only Qwen3.5 9B (4)

VRAM by quantization

Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.

QuantQwen2.5 7B InstructQwen3.5 9B

Q2_K

Qwen2.5 7B Instruct

3.7 GB3.0 GB file

32K 5.4 GB · 128K —

Qwen3.5 9B

4.7 GB4.3 GB file

32K 5.5 GB · 128K 8.7 GB

Q3_K_S

Qwen2.5 7B Instruct

3.8 GB3.5 GB file

32K 5.5 GB · 128K —

Qwen3.5 9B

4.8 GB4.3 GB file

32K 5.6 GB · 128K 8.8 GB

Q3_K_M

Qwen2.5 7B Instruct

4.1 GB3.8 GB file

32K 5.9 GB · 128K —

Qwen3.5 9B

5.3 GB4.7 GB file

32K 6.1 GB · 128K 9.3 GB

Q4_0

Qwen2.5 7B Instruct

4.2 GB4.4 GB file

32K 6.0 GB · 128K —

Qwen3.5 9B

5.4 GB5.4 GB file

32K 6.2 GB · 128K 9.4 GB

Q4_K_M

Qwen2.5 7B Instruct

5.0 GB4.7 GB file

32K 6.8 GB · 128K —

Qwen3.5 9B

6.4 GB5.7 GB file

32K 7.2 GB · 128K 10.4 GB

Q5_K_M

Qwen2.5 7B Instruct

5.8 GB5.4 GB file

32K 7.6 GB · 128K —

Qwen3.5 9B

7.5 GB6.6 GB file

32K 8.3 GB · 128K 11.5 GB

Q6_K

Qwen2.5 7B Instruct

6.7 GB6.3 GB file

32K 8.5 GB · 128K —

Qwen3.5 9B

8.5 GB7.5 GB file

32K 9.3 GB · 128K 12.6 GB

Q8_0

Qwen2.5 7B Instruct

8.0 GB8.1 GB file

32K 9.8 GB · 128K —

Qwen3.5 9B

10.2 GB9.5 GB file

32K 11.0 GB · 128K 14.3 GB

20 more quants

IQ2_XXS

Qwen2.5 7B Instruct

2.5 GB2.3 GB file

32K 4.3 GB · 128K —

Qwen3.5 9B

3.2 GB3.2 GB file

32K 4.0 GB · 128K 7.3 GB

IQ2_XS

Qwen2.5 7B Instruct

2.7 GB2.5 GB file

32K 4.5 GB · 128K —

Qwen3.5 9B

not listed

IQ2_S

Qwen2.5 7B Instruct

2.8 GB2.6 GB file

32K 4.6 GB · 128K —

Qwen3.5 9B

3.6 GB3.5 GB file

32K 4.4 GB · 128K 7.6 GB

IQ2_M

Qwen2.5 7B Instruct

3.0 GB2.8 GB file

32K 4.8 GB · 128K —

Qwen3.5 9B

3.8 GB3.6 GB file

32K 4.6 GB · 128K 7.9 GB

IQ3_XXS

Qwen2.5 7B Instruct

3.4 GB3.1 GB file

32K 5.1 GB · 128K —

Qwen3.5 9B

4.3 GB4.0 GB file

32K 5.1 GB · 128K 8.3 GB

Q2_K_S

Qwen2.5 7B Instruct

3.5 GB2.8 GB file

32K 5.2 GB · 128K —

Qwen3.5 9B

not listed

IQ3_XS

Qwen2.5 7B Instruct

3.6 GB3.3 GB file

32K 5.3 GB · 128K —

Qwen3.5 9B

4.6 GB4.8 GB file

32K 5.4 GB · 128K 8.6 GB

IQ3_S

Qwen2.5 7B Instruct

3.7 GB3.5 GB file

32K 5.4 GB · 128K —

Qwen3.5 9B

4.7 GB3.2 GB file

32K 5.5 GB · 128K 8.7 GB

IQ3_M

Qwen2.5 7B Instruct

3.8 GB3.6 GB file

32K 5.6 GB · 128K —

Qwen3.5 9B

4.9 GB5.0 GB file

32K 5.7 GB · 128K 8.9 GB

Q3_K_L

Qwen2.5 7B Instruct

4.3 GB4.1 GB file

32K 6.1 GB · 128K —

Qwen3.5 9B

5.5 GB5.4 GB file

32K 6.3 GB · 128K 9.6 GB

IQ4_XS

Qwen2.5 7B Instruct

4.5 GB4.2 GB file

32K 6.3 GB · 128K —

Qwen3.5 9B

5.8 GB5.2 GB file

32K 6.6 GB · 128K 9.8 GB

IQ4_NL

Qwen2.5 7B Instruct

4.7 GB4.5 GB file

32K 6.5 GB · 128K —

Qwen3.5 9B

6.0 GB5.4 GB file

32K 6.8 GB · 128K 10.0 GB

Q4_1

Qwen2.5 7B Instruct

4.7 GB4.9 GB file

32K 6.5 GB · 128K —

Qwen3.5 9B

6.0 GB5.8 GB file

32K 6.8 GB · 128K 10.0 GB

Q4_K_S

Qwen2.5 7B Instruct

4.7 GB4.5 GB file

32K 6.5 GB · 128K —

Qwen3.5 9B

6.0 GB5.4 GB file

32K 6.8 GB · 128K 10.0 GB

Q4_K_L

Qwen2.5 7B Instruct

5.1 GB5.1 GB file

32K 6.8 GB · 128K —

Qwen3.5 9B

6.5 GB6.9 GB file

32K 7.3 GB · 128K 10.5 GB

Q5_0

Qwen2.5 7B Instruct

5.2 GB5.3 GB file

32K 6.9 GB · 128K —

Qwen3.5 9B

not listed

Q5_1

Qwen2.5 7B Instruct

5.7 GB5.8 GB file

32K 7.4 GB · 128K —

Qwen3.5 9B

not listed

Q5_K_S

Qwen2.5 7B Instruct

5.7 GB5.3 GB file

32K 7.4 GB · 128K —

Qwen3.5 9B

7.2 GB6.4 GB file

32K 8.0 GB · 128K 11.2 GB

Q5_K_L

Qwen2.5 7B Instruct

5.9 GB5.8 GB file

32K 7.7 GB · 128K —

Qwen3.5 9B

7.6 GB7.7 GB file

32K 8.4 GB · 128K 11.6 GB

BF16

Qwen2.5 7B Instruct

15.7 GB~15.2 GB file

32K 17.4 GB · 128K —

Qwen3.5 9B

19.9 GB17.9 GB file

32K 20.7 GB · 128K 23.9 GB

How to run each

Qwen2.5 7B Instruct

Ollama · Q4_K_M

$ollama run hf.co/Qwen/Qwen2.5-7B-Instruct-GGUF:Q4_K_M

All ways to run Qwen2.5 7B Instruct →

Qwen3.5 9B

Ollama · Q4_K_M

$ollama run hf.co/unsloth/Qwen3.5-9B-GGUF:Q4_K_M

All ways to run Qwen3.5 9B →

Specifications

Specifications of Qwen2.5 7B Instruct and Qwen3.5 9B
Spec	Qwen2.5 7B Instruct	Qwen3.5 9B
Publisher	Alibaba	Alibaba
Parameters	7.6B	9.7B
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 9B?

Qwen3.5 9B leads llmrun Score 99.4 to 65.1; both fit 24 GB at Q4_K_M; Qwen2.5 7B Instruct is 1.3× faster on RTX 4090 (~131 vs ~103 tok/s). Choose Qwen2.5 7B Instruct for 1.3× faster on RTX 4090 and lighter on memory; choose Qwen3.5 9B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Qwen2.5 7B Instruct or Qwen3.5 9B?

At Q4_K_M, Qwen2.5 7B Instruct requires 5.0 GB while Qwen3.5 9B needs 6.4 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 131 tok/s for Qwen2.5 7B Instruct (Q4_K_M) and 103 tok/s for Qwen3.5 9B (Q4_K_M), so Qwen2.5 7B Instruct is faster. Estimates, ±20%.

Can I run Qwen2.5 7B Instruct or Qwen3.5 9B on a 16 GB GPU?

Qwen2.5 7B Instruct fits at Q4_K_M; Qwen3.5 9B fits at Q4_K_M.

Which has a longer context window, Qwen2.5 7B Instruct or Qwen3.5 9B?

Qwen2.5 7B Instruct supports 32,768 tokens and Qwen3.5 9B supports 262,144 tokens.