falcon mamba 7b instruct Q4 K M needs ~19.0 GB VRAM. NVIDIA DGX Spark 128GB has 108.8 GB. With Q4_K_M quantization, expect ~44 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
44.1 tok/s
TTFT
4389 ms
Safe context
1.8M
Memory
19.0 GB / 108.8 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 44.1 tok/s | 2394 ms | 1.8M |
| Coding | C | Runs well | 44.1 tok/s | 4389 ms | 1.8M |
| Agentic Coding | C | Runs well | 44.1 tok/s | 6383 ms | 1.8M |
| Reasoning | C | Runs well | 44.1 tok/s | 5186 ms | 1.8M |
| RAG | C | Runs well | 44.1 tok/s | 7979 ms | 1.8M |
How falcon mamba 7b instruct Q4 K M (7B params) fits at each quantization level on NVIDIA DGX Spark 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | D39 |
Q3_K_S | 3 | 3.4 GB | Low | D39 |
NVFP4 | 4 | 3.9 GB | Medium | D39 |
Q4_K_M | 4 | 4.3 GB | Medium | D39 |
Q5_K_M | 5 | 5.0 GB | High | D39 |
Q6_K | 6 | 5.7 GB | High | D39 |
Q8_0 | 8 | 7.5 GB | Very High | D39 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | D40 |
Copy-paste commands to run falcon mamba 7b instruct Q4 K M on your machine.
Run
lms load hf-tiiuae--falcon-mamba-7b-instruct-q4-k-m-gguf && lms server startOpciones de mejora
NVIDIA H200 141GBOpción económicaSube la velocidad estimada de decodificación alrededor de un 122%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$30,000 MSRP
NVIDIA H200 PCIe 141GBMejor relación calidad-precioSube la velocidad estimada de decodificación alrededor de un 122%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$30,000 MSRP
NVIDIA B200 180GBMejora NVIDIASube la velocidad estimada de decodificación alrededor de un 122%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$30,000 MSRP
Yes, NVIDIA DGX Spark 128GB can run falcon mamba 7b instruct Q4 K M with a C grade (Runs well). Expected decode speed: 44.1 tok/s.
falcon mamba 7b instruct Q4 K M (7B parameters) requires approximately 19.0 GB of memory with Q4_K_M quantization.
The recommended quantization for falcon mamba 7b instruct Q4 K M is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA DGX Spark 128GB, falcon mamba 7b instruct Q4 K M achieves approximately 44.1 tokens per second decode speed with a time-to-first-token of 4389ms using Q4_K_M quantization.
For coding workloads, falcon mamba 7b instruct Q4 K M on NVIDIA DGX Spark 128GB receives a C grade with 44.1 tok/s and 1.8M context.
On NVIDIA DGX Spark 128GB, falcon mamba 7b instruct Q4 K M can safely use up to 1.8M tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. NVIDIA DGX Spark 128GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.
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