Mistral Nemo Instruct 2407 vs Qwen3.6 35B A3B
Qwen3.6 35B A3B leads llmrun Score 106.8 to 65.4; both fit 24 GB at Q4_K_M; Qwen3.6 35B A3B is 1.9× faster on RTX 4090 (~151 vs ~81 tok/s).
Model A · Mistral AI
Mistral Nemo Instruct 240712.2B · 128K context · Apache 2.0 · Jul 2024
Model B · Alibaba
Qwen3.6 35B A3B36.0B · 4.7B active · 256K context · Apache 2.0 · Apr 2026
Choose Mistral Nemo Instruct 2407 if you want…
Fits a 12 GB GPU
Q4_K_M · 11 GB; Qwen3.6 35B A3B needs 10.4 GB at its smallest quant
Lighter on memory
8.1 vs 22.0 GB at Q4_K_M
Also does chat
Qwen3.6 35B A3B doesn't list it
Choose Qwen3.6 35B A3B if you want…
Higher llmrun Score
106.8 vs 65.4
1.9× faster on RTX 4090
~151 vs ~81 tok/s
Longer context window
256K vs 128K tokens
Also does vision
Mistral Nemo Instruct 2407 doesn't list it
Newer release
Apr 2026 vs Jul 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
Mistral Nemo Instruct 2407
IQ2_M · ~37 tok/s
7.8 GB · up to 16Kfits
Qwen3.6 35B A3B
Doesn't fit
smallest quant needs 10.4 GB
12 GB
RTX 3060 12GB · 12 GB tier
Mistral Nemo Instruct 2407
Q4_K_M · ~29 tok/s
11 GB · up to 16Kmore headroom
Qwen3.6 35B A3B
IQ2_S · ~114 tok/s
11.7 GB · up to 32K
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Mistral Nemo Instruct 2407
Q4_K_M · ~36 tok/s
11 GB · up to 32Kmore headroom
Qwen3.6 35B A3B
Q2_K · ~108 tok/s
15.7 GB · up to 32K
24 GBreference
RTX 4090 · 24 GB tier
Mistral Nemo Instruct 2407
Q4_K_M · ~81 tok/s
11 GB · up to 64K
Qwen3.6 35B A3B
Q4_K_M · ~151 tok/s
22 GB · up to 128Kfaster
32 GB
RTX 5090 · 32 GB tier
Mistral Nemo Instruct 2407
Q4_K_M · ~144 tok/s
11 GB · up to 64K
Qwen3.6 35B A3B
Q4_K_M · ~213 tok/s
22 GB · up to 256Kfaster
48 GB
RTX A6000 · 48 GB tier
Mistral Nemo Instruct 2407
Q4_K_M · ~62 tok/s
11 GB · up to 128K
Qwen3.6 35B A3B
Q4_K_M · ~125 tok/s
22 GB · up to 256Kfaster
Mac 32 GB
Mac Mini M4 · Macs
Mistral Nemo Instruct 2407
Q4_K_M · ~10 tok/s
11 GB · up to 64K
Qwen3.6 35B A3B
Q4_K_M · ~24 tok/s
22 GB · up to 256Kfaster
Mac 64 GB
Mac Studio M4 Max · Macs
Mistral Nemo Instruct 2407
Q4_K_M · ~47 tok/s
11 GB · up to 128K
Qwen3.6 35B A3B
Q4_K_M · ~64 tok/s
22 GB · up to 256Kfaster
Mac 128 GB
Mac Studio M4 Max · Macs
Mistral Nemo Instruct 2407
Q4_K_M · ~47 tok/s
11 GB · up to 128K
Qwen3.6 35B A3B
Q4_K_M · ~64 tok/s
22 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
Mistral Nemo Instruct 2407
Qwen3.6 35B A3B
Coding
Mistral Nemo Instruct 2407
no data
Qwen3.6 35B A3B
Math
Mistral Nemo Instruct 2407
no data
Qwen3.6 35B A3B
Science
Mistral Nemo Instruct 2407
no data
Qwen3.6 35B A3B
Reasoning
Mistral Nemo Instruct 2407
no data
Qwen3.6 35B A3B
Mistral Nemo Instruct 2407 · #101 of 106 open models · #32 of 36 that fit 24 GB
Qwen3.6 35B A3B · #41 of 106 open models · #3 of 36 that fit 24 GB
Benchmarks
2 shared boards: Mistral Nemo Instruct 2407 leads 0, Qwen3.6 35B A3B leads 2 · Benchmarks imported Nov 2026
Mistral Nemo Instruct 2407
29.9%#84/100 open
IndependentEpoch AI · Jul 2024
Qwen3.6 35B A3B
84.9%#23/100 open
IndependentEpoch AI · Apr 2026
Mistral Nemo Instruct 2407
48.6%#65/70 open
Lab-reportedEpoch AI · Jul 2024
Qwen3.6 35B A3B
73.9%#32/70 open
Lab-reportedEpoch AI · Apr 2026
12 more boards (other shared and single-model boards)
Only Mistral Nemo Instruct 2407 (3)
- MMLU-Pro44.8%
- MATH Level 510.8%
- BALROG17.6%
Only Qwen3.6 35B A3B (9)
- AIME 2024/202586.7%
- FrontierMath20.3%
- Terminal-Bench24.6%
- SciCode36.6%
- WeirdML34.5%
- CritPt0.3%
- LMCA29.7%
- Mystery Game Puzzles22.0%
- Surface Evolver Bench44.4%
VRAM by quantization
Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.
Q2_K
Mistral Nemo Instruct 2407
5.9 GB4.8 GB file
32K 12.2 GB · 128K 32.3 GB
Qwen3.6 35B A3B
15.7 GB13.5 GB file
32K 15.9 GB · 128K 16.9 GB
Q3_K_S
Mistral Nemo Instruct 2407
6.1 GB5.5 GB file
32K 12.4 GB · 128K 32.5 GB
Qwen3.6 35B A3B
16.1 GB15.4 GB file
32K 16.4 GB · 128K 17.4 GB
Q3_K_M
Mistral Nemo Instruct 2407
6.7 GB6.1 GB file
32K 13.0 GB · 128K 33.1 GB
Qwen3.6 35B A3B
17.9 GB16.6 GB file
32K 18.2 GB · 128K 19.2 GB
Q4_0
Mistral Nemo Instruct 2407
6.8 GB7.1 GB file
32K 13.1 GB · 128K 33.3 GB
Qwen3.6 35B A3B
18.4 GB19.8 GB file
32K 18.6 GB · 128K 19.6 GB
Q4_K_M
Mistral Nemo Instruct 2407
8.1 GB7.5 GB file
32K 14.4 GB · 128K 34.5 GB
Qwen3.6 35B A3B
22.0 GB22.1 GB file
32K 22.2 GB · 128K 23.2 GB
Q5_K_M
Mistral Nemo Instruct 2407
9.5 GB8.7 GB file
32K 15.7 GB · 128K 35.9 GB
Qwen3.6 35B A3B
26.0 GB26.5 GB file
32K 26.3 GB · 128K 27.3 GB
Q6_K
Mistral Nemo Instruct 2407
10.8 GB10.1 GB file
32K 17.1 GB · 128K 37.2 GB
Qwen3.6 35B A3B
30.0 GB29.3 GB file
32K 30.3 GB · 128K 31.3 GB
Q8_0
Mistral Nemo Instruct 2407
13.0 GB13.0 GB file
32K 19.3 GB · 128K 39.4 GB
Qwen3.6 35B A3B
36.3 GB36.9 GB file
32K 36.6 GB · 128K 37.6 GB
20 more quants
IQ2_XXS
Mistral Nemo Instruct 2407
4.1 GB3.6 GB file
32K 10.4 GB · 128K 30.5 GB
Qwen3.6 35B A3B
10.3 GB10.8 GB file
32K 10.5 GB · 128K 11.5 GB
IQ2_XS
Mistral Nemo Instruct 2407
4.4 GB3.9 GB file
32K 10.7 GB · 128K 30.8 GB
Qwen3.6 35B A3B
11.2 GB11.7 GB file
32K 11.4 GB · 128K 12.4 GB
IQ2_S
Mistral Nemo Instruct 2407
4.6 GB4.1 GB file
32K 10.8 GB · 128K 31.0 GB
Qwen3.6 35B A3B
11.6 GB11.9 GB file
32K 11.9 GB · 128K 12.9 GB
IQ2_M
Mistral Nemo Instruct 2407
4.9 GB4.4 GB file
32K 11.1 GB · 128K 31.3 GB
Qwen3.6 35B A3B
12.5 GB11.5 GB file
32K 12.8 GB · 128K 13.8 GB
IQ3_XXS
Mistral Nemo Instruct 2407
5.5 GB4.9 GB file
32K 11.8 GB · 128K 31.9 GB
Qwen3.6 35B A3B
14.3 GB13.2 GB file
32K 14.6 GB · 128K 15.6 GB
Q2_K_S
Mistral Nemo Instruct 2407
not listed
Qwen3.6 35B A3B
14.8 GB12.2 GB file
32K 15.0 GB · 128K 16.0 GB
IQ3_XS
Mistral Nemo Instruct 2407
5.8 GB5.3 GB file
32K 12.1 GB · 128K 32.2 GB
Qwen3.6 35B A3B
15.2 GB17.1 GB file
32K 15.5 GB · 128K 16.5 GB
IQ3_S
Mistral Nemo Instruct 2407
5.9 GB5.6 GB file
32K 12.2 GB · 128K 32.3 GB
Qwen3.6 35B A3B
15.7 GB13.7 GB file
32K 15.9 GB · 128K 16.9 GB
IQ3_M
Mistral Nemo Instruct 2407
6.2 GB5.7 GB file
32K 12.5 GB · 128K 32.7 GB
Qwen3.6 35B A3B
16.6 GB17.8 GB file
32K 16.8 GB · 128K 17.8 GB
Q3_K_L
Mistral Nemo Instruct 2407
7.0 GB6.6 GB file
32K 13.3 GB · 128K 33.4 GB
Qwen3.6 35B A3B
18.8 GB17.8 GB file
32K 19.1 GB · 128K 20.1 GB
IQ4_XS
Mistral Nemo Instruct 2407
7.3 GB6.7 GB file
32K 13.6 GB · 128K 33.7 GB
Qwen3.6 35B A3B
19.7 GB17.7 GB file
32K 20.0 GB · 128K 21.0 GB
IQ4_NL
Mistral Nemo Instruct 2407
not listed
Qwen3.6 35B A3B
20.6 GB18.0 GB file
32K 20.9 GB · 128K 21.9 GB
Q4_1
Mistral Nemo Instruct 2407
not listed
Qwen3.6 35B A3B
20.6 GB22.9 GB file
32K 20.9 GB · 128K 21.9 GB
Q4_K_S
Mistral Nemo Instruct 2407
7.6 GB7.1 GB file
32K 13.9 GB · 128K 34.0 GB
Qwen3.6 35B A3B
20.6 GB20.9 GB file
32K 20.9 GB · 128K 21.9 GB
Q4_K_L
Mistral Nemo Instruct 2407
8.2 GB8.0 GB file
32K 14.5 GB · 128K 34.6 GB
Qwen3.6 35B A3B
22.4 GB22.7 GB file
32K 22.7 GB · 128K 23.7 GB
Q5_0
Mistral Nemo Instruct 2407
8.4 GB8.5 GB file
32K 14.7 GB · 128K 34.8 GB
Qwen3.6 35B A3B
22.9 GB24.1 GB file
32K 23.1 GB · 128K 24.1 GB
Q5_1
Mistral Nemo Instruct 2407
not listed
Qwen3.6 35B A3B
25.1 GB26.1 GB file
32K 25.4 GB · 128K 26.4 GB
Q5_K_S
Mistral Nemo Instruct 2407
9.1 GB8.5 GB file
32K 15.4 GB · 128K 35.6 GB
Qwen3.6 35B A3B
25.1 GB24.9 GB file
32K 25.4 GB · 128K 26.4 GB
Q5_K_L
Mistral Nemo Instruct 2407
9.6 GB9.1 GB file
32K 15.9 GB · 128K 36.0 GB
Qwen3.6 35B A3B
26.5 GB26.2 GB file
32K 26.7 GB · 128K 27.7 GB
BF16
Mistral Nemo Instruct 2407
25.2 GB~24.5 GB file
32K 31.5 GB · 128K 51.6 GB
Qwen3.6 35B A3B
72.3 GB69.4 GB file
32K 72.5 GB · 128K 73.6 GB
Mistral Nemo Instruct 2407
Ollama · Q4_K_M
ollama run hf.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_MQwen3.6 35B A3B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.6-35B-A3B-GGUF:Q4_K_M| Spec | Mistral Nemo Instruct 2407 | Qwen3.6 35B A3B |
|---|---|---|
| Publisher | Mistral AI | Alibaba |
| Parameters | 12.2B | 36.0B |
| Active parameters | — | 4.7B per token |
| Architecture | MistralForCausalLM | Qwen3_5MoeForConditionalGeneration |
| Context | 128K tokens | 256K tokens |
| Modalities | Chat, Function-calling | Vision, Function-calling |
| License | Apache 2.0 | Apache 2.0 |
| Released | Jul 2024 | Apr 2026 |
Frequently Asked Questions
Which is better, Mistral Nemo Instruct 2407 or Qwen3.6 35B A3B?
Qwen3.6 35B A3B leads llmrun Score 106.8 to 65.4; both fit 24 GB at Q4_K_M; Qwen3.6 35B A3B is 1.9× faster on RTX 4090 (~151 vs ~81 tok/s). Choose Mistral Nemo Instruct 2407 for fits a 12 GB GPU and lighter on memory; choose Qwen3.6 35B A3B for higher llmrun Score and 1.9× faster on RTX 4090.
Which needs less VRAM, Mistral Nemo Instruct 2407 or Qwen3.6 35B A3B?
At Q4_K_M, Mistral Nemo Instruct 2407 requires 8.1 GB while Qwen3.6 35B A3B needs 22.0 GB, making Mistral Nemo Instruct 2407 the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 81 tok/s for Mistral Nemo Instruct 2407 (Q4_K_M) and 151 tok/s for Qwen3.6 35B A3B (Q4_K_M), so Qwen3.6 35B A3B is faster. Estimates, ±20%.
Can I run Mistral Nemo Instruct 2407 or Qwen3.6 35B A3B on a 16 GB GPU?
Mistral Nemo Instruct 2407 fits at Q4_K_M; Qwen3.6 35B A3B fits at Q2_K.
Which has a longer context window, Mistral Nemo Instruct 2407 or Qwen3.6 35B A3B?
Mistral Nemo Instruct 2407 supports 131,072 tokens and Qwen3.6 35B A3B supports 262,144 tokens.