MacBook Pro M3 Pro 36GBBudget pick
36 GB Unified (+12)
C
This setup is broadly balanced for this model.42 tok/s decode
~$1,999 MSRP
HelpingAI 3B hindi i1 needs ~5.8 GB VRAM. RTX 3090 24GB has 24.0 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
845K
Memory
5.8 GB / 24.0 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 | 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 |
Inference speed
Estimated decode speed (tokens/sec) for HelpingAI 3B hindi i1 at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~57 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 57.0 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 48.0 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 48.0 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 42.0 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 42.0 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 42.0 | Fits |
| RTX 4060 8GB | 8 GB | Q4_K_M | 42.0 | Fits |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 42.0 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 42.0 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 42.0 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 42.0 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 42.0 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 42.0 | Fits |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 42.0 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 42.0 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 42.0 | Fits |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How HelpingAI 3B hindi i1 (3B params) fits at each quantization level on RTX 3090 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 | C43 |
NVFP4 | 4 | 1.7 GB | Medium | C43 |
Q4_K_M | 4 | 1.8 GB | Medium | C43 |
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 |
Copy-paste commands to run HelpingAI 3B hindi i1 on your machine.
Run
lms load hf-mradermacher--helpingai-3b-hindi-i1-gguf && lms server startUpgrade options
Yes, RTX 3090 24GB can run HelpingAI 3B hindi i1 with a C grade (Runs well). Expected decode speed: 42.0 tok/s.
HelpingAI 3B hindi i1 (3B parameters) requires approximately 5.8 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI 3B hindi i1 is Q4_K_M, which balances quality and memory efficiency.
On RTX 3090 24GB, HelpingAI 3B hindi i1 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, HelpingAI 3B hindi i1 on RTX 3090 24GB receives a C grade with 42.0 tok/s and 845K context.
On RTX 3090 24GB, HelpingAI 3B hindi i1 can safely use up to 845K 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-mradermacher--helpingai-3b-hindi-i1-gguf-on-rtx-3090-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: