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OpenBMB · Vision · 35.2B parameters · Apache-2.0

MiniCPM-V 4.7 35B-A3B

Needs 43 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.

Parameters35.2Bdense
Context256k tokensmaximum published
Checkpoint70 GBBF16, as published
LicenseApache-2.0check before commercial use
ReleasedOct 6, 2026documented date
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 66% used
Per hour
$0.14
Per month
$99
Cheapest at
Vast.ai
All Tesla V100 32GB offers →

What is documented about MiniCPM-V 4.7 35B-A3B

news checked 2026-10-27

The first MoE model in the MiniCPM-V series: single-image, multi-image and video understanding, built for on-device use with Lookahead Expert Scheduling. 'A3B' is in the name; the card does not state an exact active count. 256 experts, 8 active. 30 linear + 10 full-attention layers. The weights appeared on HF around 6-7 Oct without a card (OrcaRouter); the card and Apache-2.0 tag were added later.

  • https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B
  • https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B/raw/main/config.json
  • https://huggingface.co/api/models/openbmb/MiniCPM-V-4.7-35B-A3B?blobs=true
Memory · 3 precisions · 5 context lengths

How much VRAM it needs

Weights plus runtime overhead, then the KV cache that grows with the context you serve.

PrecisionWeightsWeights + headroom4k context32k context128k context256k context
BF16published checkpoint70 GB85 GB85 GB88 GB96 GB106 GB
FP8 / INT8estimated35 GB43 GB43 GB45 GB53 GB64 GB
INT4 / MXFP4estimated21 GB26 GB26 GB29 GB37 GB47 GB
KV cacheone sequence, FP16 cache, included above——1 GB3 GB11 GB22 GB
Cross-checked on Hugging Face Oct 28, 2026: 35.2B parameters in the safetensors headers, 70.4 GB of weight files, attention layout from config.json (40 layers, 2 KV heads × 256). 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 = 2048 bytes per token per layer × 40 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 file

What 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.

GPUSmallest configVRAM used$ / hour$ / monthCheapest at
Tesla V100 32GBBest fit2× 32 GB64 GB total66%$0.14$99Vast.aiTrust 78 · read Nov 2 · receipt · also Cyfuture AI $1.13, io.net $2.52
RTX 30604× 12 GB48 GB total88%$0.16$118Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.21, Edgevana $0.31
Tesla P1004× 16 GB64 GB total66%$0.19$142Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.43
RTX 30902× 24 GB48 GB total88%$0.21$157Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.24, Lium $0.44
Quadro RTX 80001× 48 GB48 GB total88%$0.23$167Vast.aiTrust 78 · read Nov 2 · receipt · also TensorDock $0.32
Titan RTX2× 24 GB48 GB total88%$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.52
Titan Xp4× 12 GB48 GB total88%$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt
L401× 48 GB48 GB total88%$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt · also io.net $0.66, Runpod $0.69
RTX 2080 Ti4× 11 GB44 GB total96% tight$0.28$202Vast.aiTrust 78 · read Nov 2 · receipt
RTX A60001× 48 GB48 GB total88%$0.33$241GPURentonot scored · read Nov 2 · receipt · also gcube $0.34, Thunder Compute $0.35
A401× 48 GB48 GB total88%$0.35$255GPURentonot scored · read Nov 2 · receipt · also Vast.ai $0.48, Exoscale $1.05
RTX 60002× 24 GB48 GB total88%$0.35$256Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.40
RTX 5060 Ti4× 16 GB64 GB total66%$0.35$258Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.40, Edgevana $0.68
RTX A40004× 16 GB64 GB total66%$0.36$266Vast.aiTrust 78 · read Nov 2 · receipt · also AtmosCompute $0.66, Spheron $3.84
RTX A50002× 24 GB48 GB total88%$0.38$274Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.74, Airon AI $0.90
RTX 4070 Super4× 12 GB48 GB total88%$0.38$274Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.58, AtmosCompute $0.69
Tesla V100 16GB4× 16 GB64 GB total66%$0.38$275Vast.aiTrust 78 · read Nov 2 · receipt · also CloudRift $1.00, AtmosCompute $1.30
RTX 6000 Ada1× 48 GB48 GB total88%$0.40$290gcubenot scored · read Nov 2 · receipt · also Vast.ai $0.50, GPU.ai $0.65
RTX PRO 50001× 48 GB48 GB total88%$0.40$294Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.57, Clore.ai $0.63
Quadro RTX 50004× 16 GB64 GB total66%$0.40$294Vast.aiTrust 78 · read Nov 2 · receipt
RTX 3090 Ti2× 24 GB48 GB total88%$0.42$304Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.48, Edgevana $0.59
L40S1× 48 GB48 GB total88%$0.42$304Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.50, GPUBank $0.55
RTX PRO 40002× 24 GB48 GB total88%$0.45$332Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.62, Clore.ai $0.75
A800 80GB PCIe1× 80 GB80 GB total53%$0.47$342Vast.aiTrust 78 · read Nov 2 · receipt
The 24 cheapest of 73 GPU types that fit. Every GPU, any precision and context, in the finder