Nanbeige · Chat and reasoning · 33.1B parameters · Apache-2.0
Nanbeige4.3-33B
Needs 40 GB at FP8 / INT8. The smallest real configuration today is 2× Tesla V100 32GB at Vast.ai, $0.14 per hour, about $99 a month at 730 hours.
Parameters33.1Bdense
Context512k tokensmaximum published
Checkpoint66 GBBF16, as published
LicenseApache-2.0check before commercial use
ReleasedOct 24, 2026documented date
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 62% used
- Per hour
- $0.14
- Per month
- $99
- Cheapest at
Vast.ai
What is documented about Nanbeige4.3-33B
news checked 2026-10-27Dense model (Llama architecture), 512K context, aimed at agentic coding and office tasks. Card calls it 'the flagship teacher model for the Nanbeige4.3 series'; a 3B student is planned but not released. Base model published at Nanbeige/Nanbeige4.3-33B-Base. HF first commit 2026-10-24. #3 on HF trending on 2026-10-27. daily.dev describes Nanbeige as the research team of a job-recruitment app.
- https://huggingface.co/Nanbeige/Nanbeige4.3-33B
- https://huggingface.co/Nanbeige/Nanbeige4.3-33B/raw/main/config.json
- https://huggingface.co/api/models/Nanbeige/Nanbeige4.3-33B?blobs=true
Memory · 3 precisions · 6 context lengthsHow much VRAM it needs
Weights plus runtime overhead, then the KV cache that grows with the context you serve.
| Precision | Weights | Weights + headroom | 4k context | 32k context | 128k context | 256k context | 512k context |
|---|---|---|---|---|---|---|---|
| BF16published checkpoint | 66 GB | 80 GB | 81 GB | 87 GB | 108 GB | 136 GB | 192 GB |
| FP8 / INT8estimated | 33 GB | 40 GB | 41 GB | 47 GB | 68 GB | 96 GB | 152 GB |
| INT4 / MXFP4estimated | 20 GB | 24 GB | 25 GB | 31 GB | 52 GB | 80 GB | 136 GB |
| KV cacheone sequence, FP16 cache, included above | — | — | 1 GB | 7 GB | 28 GB | 56 GB | 112 GB |
Cross-checked on Hugging Face Oct 28, 2026: 33.1B parameters in the safetensors headers, 66.2 GB of weight files, attention layout from config.json (52 layers, 8 KV heads × 128). Method: weights as published at the native precision, verified on Hugging Face 2026-10-28; other precisions estimated at 1 (8-bit) and 0.6 (4-bit) bytes per parameter; × 1.2 runtime headroom; KV cache = 4096 bytes per token per layer × 52 full-attention layers (FP16 cache, one sequence).config.json ↗
Smallest configuration per GPU · 110 GPUs · cheapest eligible on-demand offer per GPU count, every provider on fileWhat it costs to run, GPU by GPU
The fewest GPUs of one type whose total memory fits the model at short context, priced from the cheapest eligible on-demand offer for exactly that count (45-day window, newest reading per provider), with the next providers beside it. Monthly = 730 hours.
| GPU | Smallest config | VRAM used | $ / hour | $ / month | Cheapest at |
|---|---|---|---|---|---|
| Tesla V100 32GBBest fit | 2× 32 GB64 GB total | 62% | $0.14 | $99 | Vast.aiTrust 78 · read Nov 2 · receipt · also Cyfuture AI $1.13, io.net $2.52 |
| RTX 3060 | 4× 12 GB48 GB total | 83% | $0.16 | $118 |  Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.21, Edgevana $0.31 |
| Tesla P100 | 4× 16 GB64 GB total | 62% | $0.19 | $142 | Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.43 |
| RTX 3090 | 2× 24 GB48 GB total | 83% | $0.21 | $157 | Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.24, Lium $0.44 |
| Quadro RTX 8000 | 1× 48 GB48 GB total | 83% | $0.23 | $167 | Vast.aiTrust 78 · read Nov 2 · receipt · also TensorDock $0.32 |
| Titan RTX | 2× 24 GB48 GB total | 83% | $0.27 | $196 | Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.52 |
| Titan Xp | 4× 12 GB48 GB total | 83% | $0.27 | $196 | Vast.aiTrust 78 · read Nov 2 · receipt |
| L40 | 1× 48 GB48 GB total | 83% | $0.27 | $196 | Vast.aiTrust 78 · read Nov 2 · receipt · also io.net $0.66, Runpod $0.69 |
| RTX 2080 Ti | 4× 11 GB44 GB total | 90% tight | $0.28 | $202 | Vast.aiTrust 78 · read Nov 2 · receipt |
| RTX A6000 | 1× 48 GB48 GB total | 83% | $0.33 | $241 |  GPURentonot scored · read Nov 2 · receipt · also gcube $0.34, Thunder Compute $0.35 |
| RTX 4000 Ada | 2× 20 GB40 GB total | 99% tight | $0.35 | $254 | Vast.aiTrust 78 · read Nov 2 · receipt · also iwinv $0.57, Akamai Cloud $1.05 |
| A40 | 1× 48 GB48 GB total | 83% | $0.35 | $255 | GPURentonot scored · read Nov 2 · receipt · also Vast.ai $0.48, Exoscale $1.05 |
| RTX 6000 | 2× 24 GB48 GB total | 83% | $0.35 | $256 | Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.40 |
| RTX 5060 Ti | 4× 16 GB64 GB total | 62% | $0.35 | $258 | Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.40, Edgevana $0.68 |
| RTX A4000 | 4× 16 GB64 GB total | 62% | $0.36 | $266 | Vast.aiTrust 78 · read Nov 2 · receipt · also AtmosCompute $0.66, Spheron $3.84 |
| RTX 3080 | 4× 10 GB40 GB total | 99% tight | $0.38 | $274 | Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.51, Edgevana $1.23 |
| RTX A5000 | 2× 24 GB48 GB total | 83% | $0.38 | $274 | Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.74, Airon AI $0.90 |
| RTX 4070 Super | 4× 12 GB48 GB total | 83% | $0.38 | $274 | Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.58, AtmosCompute $0.69 |
| Tesla V100 16GB | 4× 16 GB64 GB total | 62% | $0.38 | $275 | Vast.aiTrust 78 · read Nov 2 · receipt · also CloudRift $1.00, AtmosCompute $1.30 |
| A100 40GB | 1× 40 GB40 GB total | 99% tight | $0.39 | $283 | Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.58, AtmosCompute $0.73 |
| RTX 6000 Ada | 1× 48 GB48 GB total | 83% | $0.40 | $290 | |
| RTX PRO 5000 | 1× 48 GB48 GB total | 83% | $0.40 | $294 | Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.57, Clore.ai $0.63 |
| Quadro RTX 5000 | 4× 16 GB64 GB total | 62% | $0.40 | $294 | Vast.aiTrust 78 · read Nov 2 · receipt |
| RTX 3090 Ti | 2× 24 GB48 GB total | 83% | $0.42 | $304 | Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.48, Edgevana $0.59 |
| The 24 cheapest of 73 GPU types that fit. Every GPU, any precision and context, in the finder | |||||
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