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SELF-HOSTING

# Kimi K3.1 Pro: Self-Hosting Estimate

Kimi K3.1 Pro (Moonshot AI) on different GPUs: configuration, estimated performance and use cases.
Data updated: 2026-09-16

[← All self-hosting estimates](https://www.tandiu.cn/en/local-deploy)

Total parameters**2,780B**Sets weight VRAM

Active parameters**104B**Sets decode compute and speed

License**other**[Official repo →](https://huggingface.co/moonshotai/Kimi-K3.1-Pro)

Public benchmarks**AA 46.5 · LiveBench 74.7**

Vendor API price**$2.00 / $10.00**input / output per 1M tokens · cached $0.200 · [Token prices →](https://www.tandiu.cn/en/token-market)

Vendor API output speed**—**measured by Artificial Analysis; compare with local estimates below

## B300 288GB

288 GB · 8,000 GB/s · Top-tier Blackwell card (no official channels to China)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**8priced as 1 × 8-GPU HGX node**
Est. decode speed
**1,231 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 2,092 tok/s**in 11,250 tok/s · many concurrent requests
Hardware list price
**$299,058–$498,429**Cloud rental (live) ×8: $63.08–$63.08/hr (2026-11-04)
Hardware market price
**$1,047,167**
Typical use
Enterprise-grade ultra-large-scale training and high-concurrency inference clusters

## GB200 192GB (single card equivalent)

192 GB · 8,000 GB/s · Top-tier Blackwell card (no official channels to China)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**16 (exceeds one node: multi-node needed)**
Est. decode speed
**2,462 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 4,185 tok/s**in 25,000 tok/s · many concurrent requests
Hardware list price
**$479,088–$718,632**
Hardware market price
**$1,436,115–$2,872,231**
Typical use
Ultra-large-scale trillion-parameter model training and inference clusters (networked with Grace CPU)

## B200 180GB

180 GB · 8,000 GB/s · Top-tier Blackwell card (no official channels to China)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**16 (exceeds one node: multi-node needed)priced as 2 × 8-GPU HGX node**
Est. decode speed
**2,462 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 4,185 tok/s**in 22,500 tok/s · many concurrent requests
Hardware list price
**$598,116–$996,858**Cloud rental (live) ×16: $119.17–$200.16/hr (2026-11-05)
Hardware market price
**$897,572–$1,047,167**
Typical use
Enterprise-grade large-scale online inference and training

## H200 141GB

141 GB · 4,800 GB/s · Top-tier export-controlled card (channels to China are volatile)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**16 (exceeds one node: multi-node needed)priced as 2 × 8-GPU HGX node**
Est. decode speed
**1,477 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 2,511 tok/s**in 9,890 tok/s · many concurrent requests
Hardware list price
**$559,673–$999,417**Cloud rental (live) ×16: $47.86–$73.71/hr (2026-11-05)
Hardware market price
**$448,786–$466,737**
Typical use
Enterprise-grade production environment high-concurrency inference

## H100 SXM5 80GB

80 GB · 3,350 GB/s · Top-tier export-controlled card (no official channels to China)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**32 (exceeds one node: multi-node needed)priced as 4 × 8-GPU HGX node**
Est. decode speed
**2,062 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 3,505 tok/s**in 19,780 tok/s · many concurrent requests
Hardware list price
**$959,440–$3,326,057**Cloud rental (live) ×32: $61.89–$131.62/hr (2026-11-05)
Hardware market price
**$1,282,930**
Typical use
Enterprise-grade production environment high-concurrency inference/training

## H800 SXM 80GB

80 GB · 3,350 GB/s · Top-tier export-controlled card (discontinued)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**32 (exceeds one node: multi-node needed)priced as 4 × 8-GPU HGX node**
Est. decode speed
**2,062 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 3,505 tok/s**in 19,780 tok/s · many concurrent requests
Hardware list price
**$1,172,828–$1,244,633**
Hardware market price
**$1,615,630–$1,675,468**
Typical use
Enterprise-grade production deployment (original China-compliant model, now discontinued)

## H20 96GB

96 GB · 4,000 GB/s · Export-compliant special supply card (significantly reduced compute power)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**32 (exceeds one node: multi-node needed)**
Est. decode speed
**2,462 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 4,185 tok/s**in 2,960 tok/s · many concurrent requests
Hardware list price
**n/a**
Hardware market price
**$382,964–$526,576**
Typical use
Suboptimal choice in export-compliant environments, medium-to-large scale inference deployment (FP16 compute power is only about 15% of H100, but higher memory bandwidth offers an advantage in decode-intensive scenarios)

## A800 PCIe 80GB

80 GB · 1,935 GB/s · Compliant special supply card (export compliance status adjusted multiple times)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**32 (exceeds one node: multi-node needed)**
Est. decode speed
**1,191 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,215 tok/s**in 3,744 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**$478,705–$497,853**
Hardware market price
**$517,002–$574,446**
Typical use
Medium-scale inference/training deployment in export-compliant environments

## Ascend 910C 128GB

128 GB · 3,200 GB/s · Huawei dual-chip data center card (domestically produced)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**16 (exceeds one node: multi-node needed)**
Est. decode speed
**985 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,674 tok/s**in 7,520 tok/s · many concurrent requests
Hardware list price
**n/a**
Hardware market price
**$191,482–$478,705**
Typical use
Domestically produced large model training and inference clusters, CloudMatrix and other super-node solutions

## Ascend 910B 64GB

64 GB · 400 GB/s · Domestic alternative (not subject to US export controls)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**32 (exceeds one node: multi-node needed)**
Est. decode speed
**246 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 418 tok/s**in 6,400 tok/s · many concurrent requests
Hardware list price
**n/a**
Hardware market price
**$526,576–$574,446**
Typical use
Domestic alternative, not subject to US export controls, medium-to-large scale inference/training deployment, memory bandwidth significantly lower than NVIDIA cards of similar VRAM capacity

## RTX PRO 6000 Blackwell 96GB

96 GB · 1,792 GB/s · Professional workstation/server card (China-specific version is 6000D 84GB)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**32 (exceeds one node: multi-node needed)**
Est. decode speed
**1,103 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,125 tok/s**in 6,000 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**$512,798**Cloud rental (live) ×32: $38.50–$72.61/hr (2026-11-05)
Hardware market price
**$562,766**
Typical use
Single-card large VRAM inference, local deployment of medium MoE models, private all-in-one machine

## RTX PRO 5500 Blackwell 84GB

84 GB · 1,398 GB/s · Professional workstation card (specs are NVIDIA preliminary data)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**32 (exceeds one node: multi-node needed)**
Est. decode speed
**860 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 878 tok/s**in 5,424 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**$364,587**
Hardware market price
**$406,899–$430,835**
Typical use
Workstation large VRAM inference, departmental private deployment

## RTX PRO 5000 Blackwell 48GB

48 GB · 1,344 GB/s · Professional workstation card

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**64 (exceeds one node: multi-node needed)**
Est. decode speed
**1,654 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,687 tok/s**in 6,192 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**n/a**Cloud rental (live) ×64: $35.90–$68.42/hr (2026-11-05)
Hardware market price
**$517,002**
Typical use
Small to medium model inference, development testing, single-machine multi-card private deployment

## L40S 48GB

48 GB · 864 GB/s · Compliant inference card

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**64 (exceeds one node: multi-node needed)**
Est. decode speed
**1,063 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,085 tok/s**in 8,688 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**$430,835–$622,317**Cloud rental (live) ×64: $38.46–$58.37/hr (2026-11-05)
Hardware market price
**$430,835–$622,317**
Typical use
SME teams building inference services, medium-low concurrency

## L20 48GB

48 GB · 864 GB/s · Compliant inference card

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**64 (exceeds one node: multi-node needed)**
Est. decode speed
**1,063 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,085 tok/s**in 2,868 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**$223,527–$224,809**
Hardware market price
**$335,094**
Typical use
SME teams building inference services, medium-low concurrency

## RTX 5090 32GB

32 GB · 1,792 GB/s · Consumer flagship (not sold in China, 5090D for domestic market)

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**64 (exceeds one node: multi-node needed)**
Est. decode speed
**2,206 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 2,250 tok/s**in 10,056 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**n/a**Cloud rental (live) ×64: $28.29–$34.05/hr (2026-11-05)
Hardware market price
**$430,825**
Typical use
Local inference and development for individuals/small teams, multi-card VRAM pooling for quantized MoE

## RTX 5090D 24GB

24 GB · 1,344 GB/s · Consumer-grade/small-scale self-built

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**70 (exceeds one node: multi-node needed)**
Est. decode speed
**1,809 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,845 tok/s**in 7,796 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**$172,772**Cloud rental (live) ×70: $30.94–$37.10/hr (2026-11-05)
Hardware market price
**$293,207–$418,867**
Typical use
Personal development/small-scale verification/POC, not recommended for production-level high concurrency

## RTX 4090D 24GB

24 GB · 1,008 GB/s · Consumer-grade/small-scale self-built

Suggested precision
**INT4 (AWQ/GPTQ)**
GPUs needed
**70 (exceeds one node: multi-node needed)**
Est. decode speed
**1,357 tok/s**single-stream theoretical ceiling
Est. batched throughput
**out 1,384 tok/s**in 7,718 tok/s · many concurrent requests · PCIe multi-GPU penalty
Hardware list price
**$136,121–$198,951**Cloud rental (live) ×70: $23.66–$30.52/hr (2026-11-05)
Hardware market price
**$272,264–$314,150**
Typical use
Personal development/small-scale verification/POC, not recommended for production-level high concurrency

FAQ

## FAQ

**How is the estimated decode speed calculated?**

Estimated speed = (memory bandwidth × GPU count) ÷ (active parameters × bytes per parameter): the memory-bound upper limit for one request (roofline). It scales linearly with GPU count and ignores interconnect overhead, batching and framework losses, so real results are usually well below it.

**Can I trust the speed numbers for consumer GPUs?**

The linear assumption is reasonable for NVLink data-center cards (H/B series) but too optimistic for consumer PCIe cards without NVLink (RTX 5090D/4090D); multi-GPU consumer setups lose far more to communication, so equal-looking numbers do not mean equal performance.

**How is “Suggested precision” chosen?**

It is the highest precision that fits within 8 GPUs; beyond that it is flagged as multi-node.

**Where do the prices come from?**

USD converted at ¥6.68 per USD. Cloud rental is the international vast.ai market rate, not a China purchase price.
