TIPO V2.1 1B A200M — Hardware Requirements & GPU Compatibility
Chat
TIPO V2.1 1B A200M is a 991M-parameter open language model from KBlueLeaf. It supports a context window of up to 4,096 tokens. At Q4_K_M it needs about 0.91 GB of VRAM — see which GPUs and Macs can run it below.
Runs great on a 24 GB GPU
Runs from 8 GB (Q4_K_M · 4K)Best on 24 GB (Q4_K_M · ~864 tok/s · 4K)Macs from 8 GB (Q4_K_M · ~174 tok/s)
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run TIPO V2.1 1B A200M
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve KBlueLeaf/TIPO-v2.1-1B-A200M --max-model-len 4096vLLM repo with its own quantisation
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Fits on RTX 3060 12GB (11 GB headroom) · Q4_K_M
- Generation speed
- ~603 tok/s
- generation speed
- Cost per 1M output tokens
- $0.038
- per 1M output tokens
How Much VRAM Does TIPO V2.1 1B A200M Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | On RTX 4090 (reference) | |
|---|---|---|---|---|
| 0.7 GB | — | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Fits: 4K context · ~904 tok/s | |
| 0.8 GB | — | 3-bit medium — 3-bit medium quantization | Fits: 4K context · ~890 tok/s | |
| 0.9 GB | — | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Fits: 4K context · ~864 tok/s | |
| 1.0 GB | — | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Fits: 4K context · ~840 tok/s | |
| 1.1 GB | — | 6-bit, very good — 6-bit quantization, very good quality | Fits: 4K context · ~817 tok/s | |
| 1.3 GB | — | 8-bit, near-lossless — 8-bit quantization, near-lossless | Fits: 4K context · ~781 tok/s | |
| 2.3 GB | — | 16-bit · bfloat — Brain floating point 16 — preferred for training | Fits: 4K context · ~632 tok/s |
Selected Q4_K_M
4-bit medium quantization0.9GBat 4K context
- Weights
- 0.6 GB
- KV cache
- 0.0 GB
- Overhead
- 0.3 GB
Fits RTX 4090 (reference) · 23.1 GB free · ~864 tok/s
≥50 tok/s needs ≥15 GB/s · RTX 5090 ~965, RTX 3090 Ti ~864
Which Hardware Can Run TIPO V2.1 1B A200M?
Q4_K_M · 0.9 GBTIPO V2.1 1B A200M (Q4_K_M) requires 0.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2+ 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 TIPO V2.1 1B A200M, including NVIDIA DGX Spark, NVIDIA Jetson AGX Thor Developer Kit.
≤ 11 GB
≤ 11 GB tier →fits · 7.1 GB free · up to 4K ctx
16 GPUs · 1 Mac class · 2 device families
RTX 3080~801Simulate output on RTX 3080RTX 2080 Ti~749Simulate output on RTX 2080 TiRTX 3070 Ti~746Simulate output on RTX 3070 TiM3*8 GB~174Simulate output on iMac 24" M3 (8 GB)Orin Nano~276Simulate output on NVIDIA Jetson Orin Nano 8GB (Super)iPhone~143Simulate output on iPhone 1720 GB
fits · 19.1 GB free · up to 4K ctx
1 GPU
RX 7900 XT~279Simulate output on RX 7900 XT32–40 GB
fits · 31.1 GB free · up to 4K ctx
1 GPU · 3 Mac classes · 4 device families
RTX 5090~965Simulate output on RTX 5090M5 Max36 GB~266Simulate output on Mac Studio M5 Max (36 GB)M532 GB~204Simulate output on MacBook Air 13" M5 (32 GB)Orin~445Simulate output on NVIDIA Jetson AGX Orin 32GBSnapdragon X Elite (X1E-80-100)~272Simulate output on Snapdragon X Elite Copilot+ PC
By VRAM tier · typical GPUs and Macs at Q4_K_M
Similar models
3| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| Gemma 3 1B ITGoogle | — | 2.1 GB | ~993 | same size |
| Vaultgemma 1BGoogle | — | 3.7 GB | ~286 | same size |
| LLaMA3.1 8B Instruct DFlash UltraChatz-lab | — | 2.7 GB | ~269 | same size |
Specifications
- Publisher
- KBlueLeaf
- Parameters
- 991M
- Active parameters
- 0.2B per token
- Architecture
- KohakuForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 65,536
- Release Date
- 2026-08-22
Frequently Asked Questions
How much VRAM does TIPO V2.1 1B A200M need?
TIPO V2.1 1B A200M requires 0.9 GB of VRAM at Q4_K_M, or 2.3 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 991M × 4.8 bits ÷ 8 = 0.6 GB
KV Cache + Overhead ≈ 0.3 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.
KV Cache + Overhead ≈ 0.3 GB (at full 4K context)
VRAM usage by quantization
What's the best quantization for TIPO V2.1 1B A200M?
For TIPO V2.1 1B A200M, Q4_K_M (0.9 GB) offers the best balance of quality and VRAM usage. Q5_K_M (1.0 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 0.7 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run TIPO V2.1 1B A200M on a Mac?
Yes — MacBook Air 13" M3 (8 GB) and 145 other Macs can run TIPO V2.1 1B A200M. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 0.9 GB of usable unified memory (RAM minus macOS overhead).
Can I run TIPO V2.1 1B A200M locally?
Yes — TIPO V2.1 1B A200M can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is TIPO V2.1 1B A200M?
At Q4_K_M, TIPO V2.1 1B A200M can reach ~309 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~864 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = 1000 ÷ (active GB ÷ (bandwidth GB/s × efficiency) × 1000 + layers × routing ms)
Mixture-of-Experts: just the active experts get read for each token, along with a fixed routing cost per layer.
Example: NVIDIA B200 → 0.2 GB active ÷ (8000 × 0.65) = 0.035 ms, plus 16 layers × 0.055 ms = 0.880 ms, so 1000 ÷ 0.915 ms = ~1093 tok/s
Estimated speed at Q4_K_M (0.9 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of TIPO V2.1 1B A200M?
At Q4_K_M, the download is about 0.59 GB. The full-precision BF16 version is 1.98 GB. The smallest option (Q2_K) is 0.42 GB.
Which GPUs can run TIPO V2.1 1B A200M?
52 consumer GPUs can run TIPO V2.1 1B A200M at Q4_K_M. 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 TIPO V2.1 1B A200M?
163 devices with unified memory can run TIPO V2.1 1B A200M at Q4_K_M (0.9 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.