DeepSeek TNG R1T2 Chimera — Hardware Requirements & GPU Compatibility
Chat
DeepSeek TNG R1T2 Chimera is a 684.5B-parameter open language model from tngtech in the DeepSeek family. It supports a context window of up to 163,840 tokens. At Q4_K_M it needs about 414.60 GB of VRAM — see which GPUs and Macs can run it below.
DeepSeek TNG R1T2 Chimera runs on a 512 GB+ Mac or a multi-GPU server
Best local pick → Mac Studio (M3 Ultra, 512GB) · Q4_K_M · 412.2 GB · ~18 tok/s
Macs from 256 GB (IQ2_M · ~28 tok/s)
MIT
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run DeepSeek TNG R1T2 Chimera
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve tngtech/DeepSeek-TNG-R1T2-Chimera --max-model-len 16384 --tensor-parallel-size 8Size the nodes from the table above
Download: Q4_K_M/DeepSeek-TNG-R1T2-Chimera-Q4_K_M-00001-of-00009.gguf404.94 GB + 8 partsunsloth
Other ways
each opens step-by-stepRun in cloud
Rent 6× H100 SXM · Q4_K_M
- Estimated hourly price
- ~$16.14/hr
- est., whole server
- GPUs
- 6 GPUs
- 480 GB of VRAM
How Much VRAM Does DeepSeek TNG R1T2 Chimera Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | Runs on | |
|---|---|---|---|---|
| 294.8 GB | 293.5 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Runs on 5× H100 SXM 80 GB | |
| 303.4 GB | 302.1 GB | 3-bit small — 3-bit small quantization | Runs on 5× H100 SXM 80 GB | |
| 337.6 GB | 336.3 GB | 3-bit medium — 3-bit medium quantization | Runs on 5× H100 SXM 80 GB | |
| 346.1 GB | 344.9 GB | 4-bit · legacy — 4-bit legacy quantization | Runs on 5× H100 SXM 80 GB | |
| 414.6 GB | 413.3 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Runs on 6× H100 SXM 80 GB | |
| 491.6 GB | 490.3 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Runs on 7× H100 SXM 80 GB | |
| 568.6 GB | 567.3 GB | 6-bit, very good — 6-bit quantization, very good quality | Runs on 8× H100 SXM 80 GB | |
| 688.4 GB | 687.1 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Runs on 6× H200 SXM 141 GB |
Selected Q4_K_M
4-bit medium quantization412.2GBat 16K context
- Weights
- 410.7 GB
- KV cache
- 1.2 GB
- Overhead
- 0.3 GB
Server-class: ~412.2 GB at 16K context · about 6× H100 SXM 80 GB
Which Hardware Can Run DeepSeek TNG R1T2 Chimera?
Q4_K_M · 414.6 GBDeepSeek TNG R1T2 Chimera (Q4_K_M) requires 414.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 539+ GB is recommended. Using the full 164K context window can add up to 7.9 GB, bringing total usage to 422.5 GB. No consumer GPU has enough memory. 1 device with unified memory can run DeepSeek TNG R1T2 Chimera, including Mac Studio (M3 Ultra, 512GB).
192+ GB
Q4_K_M · best fit IQ2_XXS (189.7 GB)
4 GPUs · 1 Mac class · 2 device families
B300~181Simulate output on B300Instinct MI350X~69Simulate output on Instinct MI350XInstinct MI355X~69Simulate output on Instinct MI355XM3 Ultra256–512 GB~31Simulate output on Mac Studio (M3 Ultra, 256GB)8x H100 SXM5~250Simulate output on NVIDIA DGX H1008x A100 SXM4~226Simulate output on NVIDIA DGX A100 640GB
By VRAM tier · typical GPUs and Macs at Q4_K_M
Consumer GPUs (up to 32 GB) and Macs up to 192 GB: too small for this model (needs ≥ 189.7 GB)8 GB tier →12 GB tier →16 GB tier →24 GB tier →Macs →
Alternatives to DeepSeek TNG R1T2 Chimera
DeepSeek family · 5 models →Similar models
5| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| DeepSeek V3.2DeepSeek | 110.4 | 412.7 GB | —needs > 24 GB | same size |
| DeepSeek R1 0528DeepSeek | 103.7 | 412.2 GB | —needs > 24 GB | same size |
| Mistral Large 3 675B Instruct 2512Mistral AI | 89.6 | 454.4 GB | —needs > 24 GB | same size |
| Cogito 671B V2.1deepcogito | — | 404.1 GB | —needs > 24 GB | same size |
| A.X K2skt | — | 444 GB | —needs > 24 GB | same size |
Fine-tunes & variants(2)
Specifications
- Publisher
- tngtech
- Family
- DeepSeek
- Parameters
- 684.5B
- Active parameters
- 40.1B per token
- Architecture
- DeepseekV3ForCausalLM
- Context Length
- 163,840 tokens
- Vocabulary Size
- 129,280
- Release Date
- 2025-07-02
- License
- MIT
Frequently Asked Questions
How much VRAM does DeepSeek TNG R1T2 Chimera need?
DeepSeek TNG R1T2 Chimera requires 414.6 GB of VRAM at Q4_K_M, or 1372.9 GB at BF16. Full 164K context adds up to 7.9 GB (422.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 684.5B × 4.8 bits ÷ 8 = 410.7 GB
KV Cache + Overhead ≈ 3.9 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 ≈ 11.8 GB (at full 164K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 5090 run DeepSeek TNG R1T2 Chimera?
No — DeepSeek TNG R1T2 Chimera requires at least 192.1 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
What's the best quantization for DeepSeek TNG R1T2 Chimera?
For DeepSeek TNG R1T2 Chimera, Q4_K_M (414.6 GB) offers the best balance of quality and VRAM usage. Q5_K_S (474.5 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 192.1 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run DeepSeek TNG R1T2 Chimera on a Mac?
Yes — Mac Studio (M3 Ultra, 256GB) and 1 other Mac can run DeepSeek TNG R1T2 Chimera, the smallest at IQ2_M. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 414.6 GB of usable unified memory (RAM minus macOS overhead), from Mac Studio (M3 Ultra, 512GB).
Can I run DeepSeek TNG R1T2 Chimera locally?
Yes — DeepSeek TNG R1T2 Chimera can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
What's the download size of DeepSeek TNG R1T2 Chimera?
At Q4_K_M, the download is about 410.72 GB. The full-precision BF16 version is 1369.06 GB. The smallest option (IQ2_XXS) is 188.25 GB.
Which GPUs can run DeepSeek TNG R1T2 Chimera?
No single consumer GPU has enough VRAM to run DeepSeek TNG R1T2 Chimera at Q4_K_M (414.6 GB). Multi-GPU or professional hardware is required.
Which devices can run DeepSeek TNG R1T2 Chimera?
1 device with unified memory can run DeepSeek TNG R1T2 Chimera at Q4_K_M (414.6 GB), including Mac Studio (M3 Ultra, 512GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.