Hypernova 60B 2605 — Hardware Requirements & GPU Compatibility
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Hypernova 60B 2605 is a 58.7B-parameter open language model from MultiverseComputingCAI. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 35.59 GB of VRAM — see which GPUs and Macs can run it below.
4.9K downloads
7 likesSpecifications
- Publisher
- MultiverseComputingCAI
- Parameters
- 58.7B
- Architecture
- GptOssForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 201,088
- Release Date
- 2026-04-30
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Hypernova 60B 2605 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 25.3 GB | 31.3 GB | 24.93 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 29.0 GB | 34.9 GB | 28.60 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 35.6 GB | 41.5 GB | 35.20 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 42.2 GB | 48.1 GB | 41.79 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 48.8 GB | 54.7 GB | 48.39 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 59.0 GB | 65 GB | 58.66 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 117.7 GB | 123.7 GB | 117.32 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Hypernova 60B 2605?
Q4_K_M · 35.6 GBHypernova 60B 2605 (Q4_K_M) requires 35.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 47+ GB is recommended. Using the full 131K context window can add up to 5.9 GB, bringing total usage to 41.5 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hypernova 60B 2605?
Q4_K_M · 35.6 GB13 devices with unified memory can run Hypernova 60B 2605, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).
Runs great
— Plenty of headroom
Frequently Asked Questions
- How much VRAM does Hypernova 60B 2605 need?
Hypernova 60B 2605 requires 35.6 GB of VRAM at Q4_K_M, or 117.7 GB at BF16. Full 131K context adds up to 5.9 GB (41.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 58.7B × 4.8 bits ÷ 8 = 35.2 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 6.3 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M35.6 GBQ4_K_M + full context41.5 GB- Can NVIDIA GeForce RTX 5090 run Hypernova 60B 2605?
Yes, at Q3_K_M (29.0 GB) or lower. Higher quantizations like Q4_K_M (35.6 GB) exceed the NVIDIA GeForce RTX 5090's 32 GB.
- What's the best quantization for Hypernova 60B 2605?
For Hypernova 60B 2605, Q4_K_M (35.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (42.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 25.3 GB.
VRAM requirement by quantization
Q2_K25.3 GBQ4_K_M ★35.6 GBQ5_K_M42.2 GBQ6_K48.8 GBQ8_059.0 GBBF16117.7 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Hypernova 60B 2605 on a Mac?
Hypernova 60B 2605 requires at least 25.3 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Hypernova 60B 2605 locally?
Yes — Hypernova 60B 2605 can run locally on consumer hardware. At Q4_K_M quantization it needs 35.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hypernova 60B 2605?
At Q4_K_M, Hypernova 60B 2605 can reach ~82 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 35.6 × 0.55 = ~82 tok/s
Estimated speed at Q4_K_M (35.6 GB)
~82 tok/s~61 tok/s~51 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Hypernova 60B 2605?
At Q4_K_M, the download is about 35.20 GB. The full-precision BF16 version is 117.32 GB. The smallest option (Q2_K) is 24.93 GB.
- Which GPUs can run Hypernova 60B 2605?
No single consumer GPU has enough VRAM to run Hypernova 60B 2605 at Q4_K_M (35.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hypernova 60B 2605?
13 devices with unified memory can run Hypernova 60B 2605 at Q4_K_M (35.6 GB), including Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.