MacBook Pro M3 Pro 36GBOpción económica
36 GB Unified (+12)
C
Este setup está bastante equilibrado para este modelo.42 tok/s decodificación
~$1,999 MSRP
Can AI21 Jamba Reasoning 3B run on NVIDIA A10 24GB?
YES — Runs Great
C44Usable
Estimated from fit model
AI21 Jamba Reasoning 3B needs ~5.8 GB VRAM. NVIDIA A10 24GB has 24.0 GB. With Q4_K_M quantization, expect ~42 tok/s.
Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: Balanced
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 5.8 GB, 42.0 tok/s, Runs well
5.8 GB required24.0 GB available
24% VRAM used
Fit status
Runs well
Decode
42.0 tok/s
TTFT
4610 ms
Safe context
845K
Memory
5.8 GB / 24.0 GB
Memory breakdown
Weights1.8 GB
KV Cache0.4 GB
Runtime1.2 GB
Headroom2.4 GB
See how fast it feels
See how fast it feelsAI21 Jamba Reasoning 3B on NVIDIA A10 24GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 42.0 tok/s decode · 4.6s TTFT (warm) · 105 tok/s prefill
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 42.0 tok/s | 2514 ms | 845K |
| Coding | C | Runs well | 42.0 tok/s | 4610 ms | 845K |
| Agentic Coding | C | Runs well | 42.0 tok/s | 6705 ms | 845K |
| Reasoning | C | Runs well | 42.0 tok/s | 5448 ms | 845K |
| RAG | C | Runs well | 42.0 tok/s | 8381 ms | 845K |
Quantization options
How AI21 Jamba Reasoning 3B (3B params) fits at each quantization level on NVIDIA A10 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | C43 |
Q3_K_S | 3 | 1.5 GB | Low | C44 |
NVFP4 | 4 | 1.7 GB | Medium | C44 |
Q4_K_M | 4 | 1.8 GB | Medium | C44 |
Q5_K_M | 5 | 2.2 GB | High | C44 |
Q6_K | 6 | 2.5 GB | High | C44 |
Q8_0 | 8 | 3.2 GB | Very High | C44 |
F16Best for your GPU | 16 | 6.1 GB | Maximum | C46 |
Get started
Copy-paste commands to run AI21 Jamba Reasoning 3B on your machine.
Run
lms load hf-ai21labs--ai21-jamba-reasoning-3b-gguf && lms server startOpciones de mejora
Hardware que ejecuta bien AI21 Jamba Reasoning 3B
Frequently asked questions
Can NVIDIA A10 24GB run AI21 Jamba Reasoning 3B?
Yes, NVIDIA A10 24GB can run AI21 Jamba Reasoning 3B with a C grade (Runs well). Expected decode speed: 42.0 tok/s.
How much VRAM does AI21 Jamba Reasoning 3B need?
AI21 Jamba Reasoning 3B (3B parameters) requires approximately 5.8 GB of memory with Q4_K_M quantization.
What is the best quantization for AI21 Jamba Reasoning 3B?
The recommended quantization for AI21 Jamba Reasoning 3B is Q4_K_M, which balances quality and memory efficiency.
What speed will AI21 Jamba Reasoning 3B run at on NVIDIA A10 24GB?
On NVIDIA A10 24GB, 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.
Can NVIDIA A10 24GB run AI21 Jamba Reasoning 3B for coding?
For coding workloads, AI21 Jamba Reasoning 3B on NVIDIA A10 24GB receives a C grade with 42.0 tok/s and 845K context.
What context window can AI21 Jamba Reasoning 3B use on NVIDIA A10 24GB?
On NVIDIA A10 24GB, AI21 Jamba Reasoning 3B can safely use up to 845K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
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