Phi 4 vs Mistral Small 3.2 24B Instruct 2506
Phi 4 and Mistral Small 3.2 24B Instruct 2506 match in llmrun Score, with values of 83.8 versus 85.6; both fit 24 GB at Q4_K_M; Phi 4 is 1.6× faster on RTX 4090 (~69 vs ~43 tok/s).
Model B · Mistral AI
Mistral Small 3.2 24B Instruct 250624.0B · 128K context · Apache 2.0 · Jun 2025
Choose Phi 4 if you want…
Fits a 12 GB GPU
Q4_K_M · 12.5 GB; Mistral Small 3.2 24B Instruct 2506 needs 10.3 GB at its smallest quant
1.6× faster on RTX 4090
~69 vs ~43 tok/s
Lighter on memory
9.5 vs 15.1 GB at Q4_K_M
Also does math, code
Mistral Small 3.2 24B Instruct 2506 doesn't list it
Choose Mistral Small 3.2 24B Instruct 2506 if you want…
Longer context window
128K vs 16K tokens
Newer release
Jun 2025 vs Dec 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
Phi 4
IQ2_XXS · ~37 tok/s
7.7 GB · up to 16Kfits
Mistral Small 3.2 24B Instruct 2506
Doesn't fit
smallest quant needs 10.3 GB
12 GB
RTX 3060 12GB · 12 GB tier
Phi 4
Q4_K_M · ~25 tok/stight
12.5 GB · up to 8K
Mistral Small 3.2 24B Instruct 2506
IQ2_M · ~27 tok/s
11.8 GB · up to 16Kmore headroom
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Phi 4
Q4_K_M · ~31 tok/s
12.5 GB · up to 16Kmore headroom
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~19 tok/stight
18.1 GB · up to 4K
24 GBreference
RTX 4090 · 24 GB tier
Phi 4
Q4_K_M · ~69 tok/s
12.5 GB · up to 16Kfaster
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~43 tok/s
18.1 GB · up to 32K
32 GB
RTX 5090 · 32 GB tier
Phi 4
Q4_K_M · ~122 tok/s
12.5 GB · up to 16Kfaster
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~77 tok/s
18.1 GB · up to 64K
48 GB
RTX A6000 · 48 GB tier
Phi 4
Q4_K_M · ~52 tok/s
12.5 GB · up to 16Kfaster
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~33 tok/s
18.1 GB · up to 128K
Mac 32 GB
Mac Mini M4 · Macs
Phi 4
Q4_K_M · ~9 tok/s
12.5 GB · up to 16Kfaster
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~6 tok/s
18.1 GB · up to 64K
Mac 64 GB
Mac Studio M4 Max · Macs
Phi 4
Q4_K_M · ~40 tok/s
12.5 GB · up to 16Kfaster
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~25 tok/s
18.1 GB · up to 128K
Mac 128 GB
Mac Studio M4 Max · Macs
Phi 4
Q4_K_M · ~40 tok/s
12.5 GB · up to 16Kfaster
Mistral Small 3.2 24B Instruct 2506
Q4_K_M · ~25 tok/s
18.1 GB · up to 128K
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Phi 4
Mistral Small 3.2 24B Instruct 2506
Science
Phi 4
no data
Mistral Small 3.2 24B Instruct 2506
Reasoning
Phi 4
no data
Mistral Small 3.2 24B Instruct 2506
Phi 4 · #70 of 92 open models · #22 of 34 that fit 24 GB
Mistral Small 3.2 24B Instruct 2506 · #68 of 92 open models · #20 of 34 that fit 24 GB
Benchmarks
4 shared boards: Phi 4 leads 1, Mistral Small 3.2 24B Instruct 2506 leads 2 · Benchmarks imported Oct 2026
Phi 4
56.1%#45/97 open
IndependentEpoch AI · Dec 2024
Mistral Small 3.2 24B Instruct 2506
49.0%#54/97 open
IndependentEpoch AI · Jun 2025
Phi 4
1256.3#127/186 open
ArenaLMArena · Oct 2026
Mistral Small 3.2 24B Instruct 2506
1356.2#70/186 open
ArenaLMArena · Oct 2026
Phi 4
13.8%#56/85 open
IndependentEpoch AI · Dec 2024
Mistral Small 3.2 24B Instruct 2506
30.3%#48/85 open
IndependentEpoch AI · Jun 2025
Phi 4
1.0%#42/67 open
IndependentEpoch AI · Dec 2024
Mistral Small 3.2 24B Instruct 2506
1.0%#44/67 open
IndependentEpoch AI · Jun 2025
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
Phi 4
7.0 GB5.5 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
10.9 GB8.9 GB file
32K 17.2 GB · 128K 37.3 GB
Q3_K_S
Phi 4
7.1 GB6.5 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
11.2 GB10.4 GB file
32K 17.5 GB · 128K 37.6 GB
Q3_K_M
Phi 4
7.9 GB7.4 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
12.4 GB11.5 GB file
32K 18.7 GB · 128K 38.8 GB
Q4_0
Phi 4
8.1 GB8.4 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
12.7 GB13.5 GB file
32K 19.0 GB · 128K 39.2 GB
Q4_K_M
Phi 4
9.5 GB9.1 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
15.1 GB14.3 GB file
32K 21.4 GB · 128K 41.6 GB
Q5_K_M
Phi 4
11.2 GB10.6 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
17.8 GB16.8 GB file
32K 24.1 GB · 128K 44.3 GB
Q6_K
Phi 4
12.8 GB12.0 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
20.5 GB19.3 GB file
32K 26.8 GB · 128K 47.0 GB
Q8_0
Phi 4
15.4 GB15.6 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
24.7 GB25.1 GB file
32K 31.0 GB · 128K 51.2 GB
19 more quants
IQ2_XXS
Phi 4
4.8 GB4.1 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
7.3 GB6.8 GB file
32K 13.6 GB · 128K 33.7 GB
IQ2_XS
Phi 4
5.1 GB4.5 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
7.9 GB7.2 GB file
32K 14.2 GB · 128K 34.3 GB
IQ2_S
Phi 4
5.3 GB4.7 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
8.2 GB7.5 GB file
32K 14.5 GB · 128K 34.6 GB
IQ2_M
Phi 4
5.7 GB5.1 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
8.8 GB8.2 GB file
32K 15.1 GB · 128K 35.2 GB
IQ3_XXS
Phi 4
6.4 GB5.8 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
10.0 GB9.4 GB file
32K 16.3 GB · 128K 36.4 GB
Q2_K_S
Phi 4
6.6 GB5.2 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
10.3 GB8.3 GB file
32K 16.6 GB · 128K 36.7 GB
IQ3_XS
Phi 4
6.8 GB6.2 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
10.6 GB9.9 GB file
32K 16.9 GB · 128K 37.0 GB
IQ3_S
Phi 4
7.0 GB6.5 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
10.9 GB10.4 GB file
32K 17.2 GB · 128K 37.3 GB
IQ3_M
Phi 4
7.3 GB6.9 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
11.5 GB10.7 GB file
32K 17.8 GB · 128K 37.9 GB
Q3_K_L
Phi 4
8.2 GB7.9 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
13.0 GB12.4 GB file
32K 19.3 GB · 128K 39.5 GB
IQ4_XS
Phi 4
8.6 GB7.9 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
13.6 GB12.8 GB file
32K 19.9 GB · 128K 40.1 GB
IQ4_NL
Phi 4
9.0 GB8.4 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
14.2 GB13.5 GB file
32K 20.5 GB · 128K 40.7 GB
Q4_1
Phi 4
9.0 GB9.3 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
14.2 GB14.9 GB file
32K 20.5 GB · 128K 40.7 GB
Q4_K_S
Phi 4
9.0 GB8.4 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
14.2 GB13.5 GB file
32K 20.5 GB · 128K 40.7 GB
Q4_K_L
Phi 4
9.7 GB9.4 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
15.4 GB14.8 GB file
32K 21.7 GB · 128K 41.9 GB
Q5_0
Phi 4
9.9 GB10.2 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
15.7 GB16.4 GB file
32K 22.0 GB · 128K 42.2 GB
Q5_K_S
Phi 4
10.8 GB10.2 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
17.2 GB16.3 GB file
32K 23.5 GB · 128K 43.7 GB
Q5_K_L
Phi 4
11.4 GB10.9 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
18.1 GB17.2 GB file
32K 24.4 GB · 128K 44.6 GB
BF16
Phi 4
30.0 GB~29.3 GB file
32K — · 128K —
Mistral Small 3.2 24B Instruct 2506
48.7 GB47.2 GB file
32K 55.0 GB · 128K 75.2 GB
Phi 4
Ollama · Q4_K_M
ollama run hf.co/MaziyarPanahi/phi-4-GGUF:Q4_K_MMistral 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_M| Spec | Phi 4 | Mistral Small 3.2 24B Instruct 2506 |
|---|---|---|
| Publisher | Microsoft | Mistral AI |
| Parameters | 14.7B | 24.0B |
| Architecture | Phi3ForCausalLM | Mistral3ForConditionalGeneration |
| Context | 16K tokens | 128K tokens |
| Modalities | Chat, Math, Code | Chat |
| License | MIT | Apache 2.0 |
| Released | Dec 2024 | Jun 2025 |
Frequently Asked Questions
Which is better, Phi 4 or Mistral Small 3.2 24B Instruct 2506?
Phi 4 and Mistral Small 3.2 24B Instruct 2506 match in llmrun Score, with values of 83.8 versus 85.6; both fit 24 GB at Q4_K_M; Phi 4 is 1.6× faster on RTX 4090 (~69 vs ~43 tok/s). Choose Phi 4 for fits a 12 GB GPU and 1.6× faster on RTX 4090; choose Mistral Small 3.2 24B Instruct 2506 for longer context window and newer release.
Which needs less VRAM, Phi 4 or Mistral Small 3.2 24B Instruct 2506?
At Q4_K_M, Phi 4 requires 9.5 GB while Mistral Small 3.2 24B Instruct 2506 needs 15.1 GB, making Phi 4 the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 69 tok/s for Phi 4 (Q4_K_M) and 43 tok/s for Mistral Small 3.2 24B Instruct 2506 (Q4_K_M), so Phi 4 is faster. Estimates, ±20%.
Can I run Phi 4 or Mistral Small 3.2 24B Instruct 2506 on a 16 GB GPU?
Phi 4 fits at Q4_K_M; Mistral Small 3.2 24B Instruct 2506 fits at Q4_K_M.
Which has a longer context window, Phi 4 or Mistral Small 3.2 24B Instruct 2506?
Phi 4 supports 16,384 tokens and Mistral Small 3.2 24B Instruct 2506 supports 131,072 tokens.