H2ovl Mississippi 800M — Hardware Requirements & GPU Compatibility
ChatVision
H2ovl Mississippi 800M is a 826M-parameter open language model from h2oai. At BF16 it needs about 1.82 GB of VRAM — see which GPUs and Macs can run it below.
Runs great on a 24 GB GPU
Runs from 8 GB (BF16 · 32K)Best on 24 GB (BF16 · ~360 tok/s · 32K)Macs from 8 GB (BF16 · ~39 tok/s)
Apache 2.0
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run H2ovl Mississippi 800M
One recommended way. Every other method, OS and quant is in the step-by-step guide.Each way opens a step-by-step guide for your OS and quant.
Recommended
vllm serve h2oai/h2ovl-mississippi-800m --max-model-len 16384vLLM repo with its own quantisation
Download: Weights on Hugging Face
Ways to runOther ways
each opens step-by-stepRun in cloud
Runs on RTX 3080 Ti (12 GB) (8 GB headroom) · BF16
- Generation speed
- ~326 tok/s
- generation speed
- Cost per 1M output tokens
- $0.10
- per 1M output tokens
How Much VRAM Does H2ovl Mississippi 800M Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | On RTX 4090 (reference) | |
|---|---|---|---|---|
| 1.8 GB | 4.7 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Fits: 32K context · ~360 tok/s |
Selected BF16
Brain floating point 163.2GBat 16K context
- Weights
- 1.3 GB
- KV cache
- 1.6 GB
- Overhead
- 0.3 GB
Fits RTX 4090 (reference) · 20.8 GB free · ~360 tok/s
≥50 tok/s needs ≥140 GB/s · RTX 5090 ~640, RTX 3090 Ti ~360
Which Hardware Can Run H2ovl Mississippi 800M?
BF16 · 1.8 GBH2ovl Mississippi 800M (BF16) requires 1.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ GB is recommended. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti. 163 devices with unified memory can run H2ovl Mississippi 800M, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB).
≤ 11 GB
≤ 11 GB tier →fits · 4.8 GB free · up to 32K ctx
16 GPUs · 1 Mac class · 2 device families
RTX 3080~272Simulate output on RTX 3080RTX 2080 Ti~220Simulate output on RTX 2080 TiRTX 3070 Ti~217Simulate output on RTX 3070 TiM3*8 GB~39Simulate output on iMac 24" M3 (8 GB)Orin Nano~36Simulate output on NVIDIA Jetson Orin Nano 8GB (Super)iPhone~26Simulate output on iPhone 1720 GB
fits · 16.8 GB free · up to 32K ctx
1 GPU
RX 7900 XT~264Simulate output on RX 7900 XT32–40 GB
fits · 28.8 GB free · up to 32K ctx
1 GPU · 3 Mac classes · 4 device families
RTX 5090~640Simulate output on RTX 5090M5 Max36 GB~177Simulate output on Mac Studio M5 Max (36 GB)M532 GB~59Simulate output on MacBook Air 13" M5 (32 GB)Orin~73Simulate output on NVIDIA Jetson AGX Orin 32GBSnapdragon X Elite (X1E-80-100)~48Simulate output on Snapdragon X Elite Copilot+ PC
By VRAM tier · typical GPUs and Macs at BF16
Similar models
1| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| Qwen3.5 0.8BAlibaba | — | 0.9 GB | ~753 | same size |
Specifications
- Publisher
- h2oai
- Parameters
- 826M
- Architecture
- H2OVLChatModel
- Release Date
- 2024-10-16
- License
- Apache 2.0
Frequently Asked Questions
How much VRAM does H2ovl Mississippi 800M need?
H2ovl Mississippi 800M requires 1.8 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 826M × 16 bits ÷ 8 = 1.7 GB
KV Cache + Overhead ≈ 0.1 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
VRAM usage by quantization
Can I run H2ovl Mississippi 800M on a Mac?
Yes — Mac Mini M2 (8 GB) and 145 other Macs can run H2ovl Mississippi 800M. Apple Silicon uses unified memory, so the model shares RAM with the system. At BF16 you need at least 1.8 GB of usable unified memory (RAM minus macOS overhead).
Can I run H2ovl Mississippi 800M locally?
Yes — H2ovl Mississippi 800M can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is H2ovl Mississippi 800M?
At BF16, H2ovl Mississippi 800M can reach ~2637 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~360 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 1.82 × 0.65 = ~2857 tok/s
Estimated speed at BF16 (1.8 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of H2ovl Mississippi 800M?
At BF16, the download is about 1.65 GB.
Which GPUs can run H2ovl Mississippi 800M?
52 consumer GPUs can run H2ovl Mississippi 800M at BF16. Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.
Which devices can run H2ovl Mississippi 800M?
163 devices with unified memory can run H2ovl Mississippi 800M at BF16 (1.8 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.