MacBook Pro M4 Max 96GBBudget pick
96 GB Unified (+48)
C
Adds memory headroom for longer context windows and future model growth.42 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
AI21 Jamba Reasoning 3B needs ~8.2 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~42 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
42.0 tok/s
TTFT
4610 ms
Safe context
1.8M
Memory
8.2 GB / 48.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 42.0 tok/s | 2514 ms | 1.8M |
| Coding | C | Runs well | 42.0 tok/s | 4610 ms | 1.8M |
| Agentic Coding | C | Runs well | 42.0 tok/s | 6705 ms | 1.8M |
| Reasoning | C | Runs well | 42.0 tok/s | 5448 ms | 1.8M |
| RAG | C | Runs well | 42.0 tok/s | 8381 ms | 1.8M |
How AI21 Jamba Reasoning 3B (3B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | C41 |
Q3_K_S | 3 | 1.5 GB | Low | C41 |
NVFP4 | 4 |
Copy-paste commands to run AI21 Jamba Reasoning 3B on your machine.
Run
lms load hf-ai21labs--ai21-jamba-reasoning-3b-gguf && lms server startUpgrade options
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Yes, NVIDIA A40 48GB can run AI21 Jamba Reasoning 3B with a C grade (Runs well). Expected decode speed: 42.0 tok/s.
AI21 Jamba Reasoning 3B (3B parameters) requires approximately 8.2 GB of memory with Q4_K_M quantization.
The recommended quantization for AI21 Jamba Reasoning 3B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A40 48GB, AI21 Jamba Reasoning 3B achieves approximately 42.0 tokens per second decode speed with a time-to-first-token of 4610ms using Q4_K_M quantization.
For coding workloads, AI21 Jamba Reasoning 3B on NVIDIA A40 48GB receives a C grade with 42.0 tok/s and 1.8M context.
On NVIDIA A40 48GB, AI21 Jamba Reasoning 3B can safely use up to 1.8M tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-ai21labs--ai21-jamba-reasoning-3b-gguf-on-a40-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
1.7 GB |
| Medium |
| C41 |
Q4_K_M | 4 | 1.8 GB | Medium | C41 |
Q5_K_M | 5 | 2.2 GB | High | C41 |
Q6_K | 6 | 2.5 GB | High | C41 |
Q8_0 | 8 | 3.2 GB | Very High | C41 |
F16Best for your GPU | 16 | 6.1 GB | Maximum | C42 |