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Recursive · Code · 39.8B parameters · 2.5B active · Apache-2.0

Flint

Needs 48 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.

Parameters39.8B2.5B active per token
Context256k tokensmaximum published
Checkpoint80 GBBF16, as published
LicenseApache-2.0check before commercial use
ReleasedOct 21, 2026documented date
Downloads14,047RecursiveSI/flint ↗
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 75% used
Per hour
$0.14
Per month
$99
Cheapest at
Vast.ai
All Tesla V100 32GB offers →

What is documented about Flint

news checked 2026-10-27

Trained from scratch for coding agents. Card: 39.8B total, about 2.5B active including the output head. 49 layers = 2 dense + 47 MoE (35 sliding + 14 full attention). 256 experts, 6 active, plus a shared expert. #2 on HF trending on 2026-10-27. Benchmarks are self-reported.

  • https://huggingface.co/RecursiveSI/flint
  • https://huggingface.co/RecursiveSI/flint/raw/main/config.json
  • https://huggingface.co/api/models/RecursiveSI/flint?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 checkpoint80 GB96 GB96 GB97 GB100 GB104 GB
FP8 / INT8estimated40 GB48 GB48 GB49 GB52 GB56 GB
INT4 / MXFP4estimated24 GB29 GB29 GB30 GB33 GB37 GB
KV cacheone sequence, FP16 cache, included above——1 GB1 GB4 GB8 GB
Cross-checked on Hugging Face Oct 28, 2026: 39.8B parameters in the safetensors headers, 79.6 GB of weight files, attention layout from config.json (49 layers, 4 KV heads × 128, 35 sliding-window layers). 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 × 14 full-attention layers + 35 sliding-window layers capped at 513 tokens (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 total75%$0.14$99Vast.aiTrust 78 · read Nov 1 · receipt · also Cyfuture AI $1.13, io.net $2.52
T44× 16 GB64 GB total75%$0.16$117Vast.aiTrust 78 · read Nov 1 · receipt · also iwinv $0.78, NHN Cloud $2.46
RTX 30604× 12 GB48 GB total100% tight$0.16$119Clore.aiTrust 46 · read Nov 1 · receipt · also Vast.ai $0.21, Edgevana $0.37
Tesla P1004× 16 GB64 GB total75%$0.19$138Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.37
RTX 30902× 24 GB48 GB total100% tight$0.21$157Vast.aiTrust 78 · read Nov 1 · receipt · also Clore.ai $0.24, Edgevana $0.46
Quadro RTX 80001× 48 GB48 GB total100% tight$0.25$186Vast.aiTrust 78 · read Nov 1 · receipt · also TensorDock $0.32
RTX 60002× 24 GB48 GB total100% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt
Titan RTX2× 24 GB48 GB total100% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.55
Titan Xp4× 12 GB48 GB total100% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt
L401× 48 GB48 GB total100% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt · also io.net $0.66, GPURento $0.69
RTX A60001× 48 GB48 GB total100% tight$0.33$241GPURentonot scored · read Nov 1 · receipt · also gcube $0.34, Thunder Compute $0.35
A401× 48 GB48 GB total100% tight$0.35$255GPURentonot scored · read Nov 1 · receipt · also Vast.ai $0.48, Exoscale $1.05
RTX 5060 Ti4× 16 GB64 GB total75%$0.35$258Clore.aiTrust 46 · read Nov 1 · receipt · also Vast.ai $0.38, Edgevana $0.68
RTX A40004× 16 GB64 GB total75%$0.36$266Vast.aiTrust 78 · read Nov 1 · receipt · also Spheron $3.84
RTX A50002× 24 GB48 GB total100% tight$0.38$274Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.74, Airon AI $0.90
RTX 4070 Super4× 12 GB48 GB total100% tight$0.38$274Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.56, Clore.ai $0.58
Tesla V100 16GB4× 16 GB64 GB total75%$0.38$275Vast.aiTrust 78 · read Nov 1 · receipt · also CloudRift $1.00, AtmosCompute $1.30
RTX 6000 Ada1× 48 GB48 GB total100% tight$0.40$290gcubenot scored · read Nov 1 · receipt · also Vast.ai $0.50, GPU.ai $0.65
Quadro RTX 50004× 16 GB64 GB total75%$0.40$294Vast.aiTrust 78 · read Nov 1 · receipt
RTX 3090 Ti2× 24 GB48 GB total100% tight$0.42$304Clore.aiTrust 46 · read Nov 1 · receipt
L40S1× 48 GB48 GB total100% tight$0.43$314Vast.aiTrust 78 · read Nov 1 · receipt · also Clore.ai $0.50, GPUBank $0.55
RTX PRO 40002× 24 GB48 GB total100% tight$0.45$332Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.62, Clore.ai $0.75
A800 80GB PCIe1× 80 GB80 GB total60%$0.47$342Vast.aiTrust 78 · read Nov 1 · receipt
A102× 24 GB48 GB total100% tight$0.48$352Vast.aiTrust 78 · read Nov 1 · receipt · also Volcano Engine $3.19, Microsoft Azure $6.52
The 24 cheapest of 73 GPU types that fit. Every GPU, any precision and context, in the finder