Mistral Small 3.2 24B Instruct 2506 vs Qwen3.8 27B
Qwen3.8 27B leads llmrun Score 121.5 to 85.6; both fit 24 GB at Q4_K_M.
Model A · Mistral AI
Mistral Small 3.2 24B Instruct 250624.0B · 128K context · Apache 2.0 · Jun 2025
Model B · Alibaba
Qwen3.8 27B27.8B · 256K context · Apache 2.0 · Aug 2026
Choose Mistral Small 3.2 24B Instruct 2506 if you want…
Also does chat
Qwen3.8 27B doesn't list it
Choose Qwen3.8 27B if you want…
Higher llmrun Score
121.5 vs 85.6
Stronger at reasoning
124.1 vs 83.0
Stronger at science
112.0 vs 82.4
Ahead on the benchmarks
4 of 4 shared boards
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Mistral Small 3.2 24B Instruct 2506 needs 10.3 GB at its smallest quant
Longer context window
256K vs 128K tokens
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
Mistral Small 3.2 24B Instruct 2506
Doesn't fit
smallest quant needs 10.3 GB
Qwen3.8 27B
Doesn't fit
smallest quant needs 8.8 GB
12 GB
RTX 3060 12GB · 12 GB tier
Mistral Small 3.2 24B Instruct 2506
IQ2_M · ~27 tok/s
11.8 GB · up to 16K
Qwen3.8 27B
IQ3_XXS · ~20 tok/s
12 GB · up to 16Kbetter quant
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~19 tok/stight
18.1 GB · up to 4K
Qwen3.8 27B
Q3_K_L · ~19 tok/s
15.4 GB · up to 16Kmore headroom
24 GBreference
RTX 4090 · 24 GB tier
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~43 tok/s
18.1 GB · up to 32Kfaster
Qwen3.8 27B
Q4_K_M · ~38 tok/s
17.9 GB · up to 64K
32 GB
RTX 5090 · 32 GB tier
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~77 tok/s
18.1 GB · up to 64Kfaster
Qwen3.8 27B
Q4_K_M · ~67 tok/s
17.9 GB · up to 256K
48 GB
RTX A6000 · 48 GB tier
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~33 tok/s
18.1 GB · up to 128Kfaster
Qwen3.8 27B
Q4_K_M · ~29 tok/s
17.9 GB · up to 256K
Mac 32 GB
Mac Mini M4 · Macs
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~6 tok/s
18.1 GB · up to 64Kfaster
Qwen3.8 27B
Q4_K_M · ~5 tok/s
17.9 GB · up to 128K
Mac 64 GB
Mac Studio M4 Max · Macs
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~25 tok/s
18.1 GB · up to 128Kfaster
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256K
Mac 128 GB
Mac Studio M4 Max · Macs
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~25 tok/s
18.1 GB · up to 128Kfaster
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256K
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Mistral Small 3.2 24B Instruct 2506
Qwen3.8 27B
Coding
Mistral Small 3.2 24B Instruct 2506
no data
Qwen3.8 27B
Math
Mistral Small 3.2 24B Instruct 2506
no data
Qwen3.8 27B
Science
Mistral Small 3.2 24B Instruct 2506
Qwen3.8 27B
Reasoning
Mistral Small 3.2 24B Instruct 2506
Qwen3.8 27B
Mistral Small 3.2 24B Instruct 2506 · #68 of 92 open models · #20 of 34 that fit 24 GB
Qwen3.8 27B · #10 of 92 open models · #1 of 34 that fit 24 GB
Benchmarks
4 shared boards: Mistral Small 3.2 24B Instruct 2506 leads 0, Qwen3.8 27B leads 4 · Benchmarks imported Oct 2026
Mistral Small 3.2 24B Instruct 2506
1356.2#70/186 open
ArenaLMArena · Oct 2026
Qwen3.8 27B
1438.1#22/186 open
ArenaLMArena · Oct 2026
Mistral Small 3.2 24B Instruct 2506
26.4%#56/65 open
Lab-reportedEpoch AI · Jun 2025
Qwen3.8 27B
46.6%#19/65 open
Lab-reportedEpoch AI · Aug 2026
Mistral Small 3.2 24B Instruct 2506
0.0%#60/65 open
Lab-reportedEpoch AI · Jun 2025
Qwen3.8 27B
5.4%#15/65 open
Lab-reportedEpoch AI · Aug 2026
Mistral Small 3.2 24B Instruct 2506
59.9%#49/68 open
Lab-reportedEpoch AI · Jun 2025
Qwen3.8 27B
88.0%#9/68 open
Lab-reportedEpoch AI · Aug 2026
13 more boards (other shared and single-model boards)
Only Mistral Small 3.2 24B Instruct 2506 (3)
- GPQA Diamond49.0%
- AIME 2024/202530.3%
- Chess Puzzles1.0%
Only Qwen3.8 27B (10)
- LiveBench Coding75.7
- LiveBench Reasoning80.0
- LMArena WebDev1592.8
- LiveBench Math86.2
- ARC-AGI-242.4%
- ARC-AGI87.5%
- LMCA41.4%
- APEX-Agents47.5%
- Surface Evolver Bench45.0%
- ProofBench16.0%
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
Mistral Small 3.2 24B Instruct 2506
10.9 GB8.9 GB file
32K 17.2 GB · 128K 37.3 GB
Qwen3.8 27B
12.6 GB10.8 GB file
32K 13.9 GB · 128K 19.3 GB
Q3_K_S
Mistral Small 3.2 24B Instruct 2506
11.2 GB10.4 GB file
32K 17.5 GB · 128K 37.6 GB
Qwen3.8 27B
12.9 GB12.7 GB file
32K 14.2 GB · 128K 19.6 GB
Q3_K_M
Mistral Small 3.2 24B Instruct 2506
12.4 GB11.5 GB file
32K 18.7 GB · 128K 38.8 GB
Qwen3.8 27B
14.3 GB13.4 GB file
32K 15.6 GB · 128K 21.0 GB
Q4_0
Mistral Small 3.2 24B Instruct 2506
12.7 GB13.5 GB file
32K 19.0 GB · 128K 39.2 GB
Qwen3.8 27B
14.6 GB~13.9 GB file
32K 16.0 GB · 128K 21.4 GB
Q4_K_M
Mistral Small 3.2 24B Instruct 2506
15.1 GB14.3 GB file
32K 21.4 GB · 128K 41.6 GB
Qwen3.8 27B
17.4 GB16.5 GB file
32K 18.8 GB · 128K 24.1 GB
Q5_K_M
Mistral Small 3.2 24B Instruct 2506
17.8 GB16.8 GB file
32K 24.1 GB · 128K 44.3 GB
Qwen3.8 27B
20.5 GB19.8 GB file
32K 21.9 GB · 128K 27.3 GB
Q6_K
Mistral Small 3.2 24B Instruct 2506
20.5 GB19.3 GB file
32K 26.8 GB · 128K 47.0 GB
Qwen3.8 27B
23.7 GB22.0 GB file
32K 25.0 GB · 128K 30.4 GB
Q8_0
Mistral Small 3.2 24B Instruct 2506
24.7 GB25.1 GB file
32K 31.0 GB · 128K 51.2 GB
Qwen3.8 27B
28.5 GB29.0 GB file
32K 29.9 GB · 128K 35.2 GB
19 more quants
IQ2_XXS
Mistral Small 3.2 24B Instruct 2506
7.3 GB6.8 GB file
32K 13.6 GB · 128K 33.7 GB
Qwen3.8 27B
8.4 GB7.3 GB file
32K 9.7 GB · 128K 15.1 GB
IQ2_XS
Mistral Small 3.2 24B Instruct 2506
7.9 GB7.2 GB file
32K 14.2 GB · 128K 34.3 GB
Qwen3.8 27B
9.1 GB9.1 GB file
32K 10.4 GB · 128K 15.8 GB
IQ2_S
Mistral Small 3.2 24B Instruct 2506
8.2 GB7.5 GB file
32K 14.5 GB · 128K 34.6 GB
Qwen3.8 27B
9.4 GB8.4 GB file
32K 10.8 GB · 128K 16.1 GB
IQ2_M
Mistral Small 3.2 24B Instruct 2506
8.8 GB8.2 GB file
32K 15.1 GB · 128K 35.2 GB
Qwen3.8 27B
10.1 GB10.5 GB file
32K 11.5 GB · 128K 16.8 GB
IQ3_XXS
Mistral Small 3.2 24B Instruct 2506
10.0 GB9.4 GB file
32K 16.3 GB · 128K 36.4 GB
Qwen3.8 27B
11.5 GB10.9 GB file
32K 12.9 GB · 128K 18.2 GB
Q2_K_S
Mistral Small 3.2 24B Instruct 2506
10.3 GB8.3 GB file
32K 16.6 GB · 128K 36.7 GB
Qwen3.8 27B
not listed
IQ3_XS
Mistral Small 3.2 24B Instruct 2506
10.6 GB9.9 GB file
32K 16.9 GB · 128K 37.0 GB
Qwen3.8 27B
12.2 GB10.4 GB file
32K 13.6 GB · 128K 18.9 GB
IQ3_S
Mistral Small 3.2 24B Instruct 2506
10.9 GB10.4 GB file
32K 17.2 GB · 128K 37.3 GB
Qwen3.8 27B
12.6 GB12.0 GB file
32K 13.9 GB · 128K 19.3 GB
IQ3_M
Mistral Small 3.2 24B Instruct 2506
11.5 GB10.7 GB file
32K 17.8 GB · 128K 37.9 GB
Qwen3.8 27B
13.3 GB14.9 GB file
32K 14.6 GB · 128K 20.0 GB
Q3_K_L
Mistral Small 3.2 24B Instruct 2506
13.0 GB12.4 GB file
32K 19.3 GB · 128K 39.5 GB
Qwen3.8 27B
15.0 GB14.1 GB file
32K 16.3 GB · 128K 21.7 GB
IQ4_XS
Mistral Small 3.2 24B Instruct 2506
13.6 GB12.8 GB file
32K 19.9 GB · 128K 40.1 GB
Qwen3.8 27B
15.7 GB14.3 GB file
32K 17.0 GB · 128K 22.4 GB
IQ4_NL
Mistral Small 3.2 24B Instruct 2506
14.2 GB13.5 GB file
32K 20.5 GB · 128K 40.7 GB
Qwen3.8 27B
16.4 GB17.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_1
Mistral Small 3.2 24B Instruct 2506
14.2 GB14.9 GB file
32K 20.5 GB · 128K 40.7 GB
Qwen3.8 27B
16.4 GB17.5 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_S
Mistral Small 3.2 24B Instruct 2506
14.2 GB13.5 GB file
32K 20.5 GB · 128K 40.7 GB
Qwen3.8 27B
16.4 GB15.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_L
Mistral Small 3.2 24B Instruct 2506
15.4 GB14.8 GB file
32K 21.7 GB · 128K 41.9 GB
Qwen3.8 27B
17.8 GB18.8 GB file
32K 19.1 GB · 128K 24.5 GB
Q5_0
Mistral Small 3.2 24B Instruct 2506
15.7 GB16.4 GB file
32K 22.0 GB · 128K 42.2 GB
Qwen3.8 27B
not listed
Q5_K_S
Mistral Small 3.2 24B Instruct 2506
17.2 GB16.3 GB file
32K 23.5 GB · 128K 43.7 GB
Qwen3.8 27B
19.9 GB18.7 GB file
32K 21.2 GB · 128K 26.6 GB
Q5_K_L
Mistral Small 3.2 24B Instruct 2506
18.1 GB17.2 GB file
32K 24.4 GB · 128K 44.6 GB
Qwen3.8 27B
20.9 GB21.5 GB file
32K 22.2 GB · 128K 27.6 GB
BF16
Mistral Small 3.2 24B Instruct 2506
48.7 GB47.2 GB file
32K 55.0 GB · 128K 75.2 GB
Qwen3.8 27B
56.3 GB54.7 GB file
32K 57.7 GB · 128K 63.0 GB
Mistral Small 3.2 24B Instruct 2506
Ollama · Q4_K_M
ollama run hf.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:Q4_K_MQwen3.8 27B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_M| Spec | Mistral Small 3.2 24B Instruct 2506 | Qwen3.8 27B |
|---|---|---|
| Publisher | Mistral AI | Alibaba |
| Parameters | 24.0B | 27.8B |
| Architecture | Mistral3ForConditionalGeneration | Qwen3_5ForConditionalGeneration |
| Context | 128K tokens | 256K tokens |
| Modalities | Chat | Vision, Function-calling |
| License | Apache 2.0 | Apache 2.0 |
| Released | Jun 2025 | Aug 2026 |
Frequently Asked Questions
Which is better, Mistral Small 3.2 24B Instruct 2506 or Qwen3.8 27B?
Qwen3.8 27B leads llmrun Score 121.5 to 85.6; both fit 24 GB at Q4_K_M. Choose Mistral Small 3.2 24B Instruct 2506 for also does chat; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.
Which needs less VRAM, Mistral Small 3.2 24B Instruct 2506 or Qwen3.8 27B?
At Q4_K_M, Mistral Small 3.2 24B Instruct 2506 requires 15.1 GB while Qwen3.8 27B needs 17.4 GB, making Mistral Small 3.2 24B Instruct 2506 the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 43 tok/s for Mistral Small 3.2 24B Instruct 2506 (Q4_K_M) and 38 tok/s for Qwen3.8 27B (Q4_K_M), so Mistral Small 3.2 24B Instruct 2506 is faster. Estimates, ±20%.
Can I run Mistral Small 3.2 24B Instruct 2506 or Qwen3.8 27B on a 16 GB GPU?
Mistral Small 3.2 24B Instruct 2506 fits at Q4_K_M; Qwen3.8 27B fits at Q3_K_L.
Which has a longer context window, Mistral Small 3.2 24B Instruct 2506 or Qwen3.8 27B?
Mistral Small 3.2 24B Instruct 2506 supports 131,072 tokens and Qwen3.8 27B supports 262,144 tokens.