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Model Pareto

NVIDIA Nemotron-Labs Dory1.0 4B

NVIDIAOpen weightshuggingface.co ↗
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Input
—
Output
—
Speed
~190tok/sest.
Context
256Ktokens

Rankings

Self-hostingEstimated

How we estimate →

What it would cost to run these open weights yourself on rented GPUs. No API sells this model, so this is its price on the chart.

Hardware
1× B200 180GB
BF16 weights
Throughput
~15,768 tok/s
many requests batched
Price
$0.048–0.43 /M tok
busy → light use
On your own machine
RTX 5090 32GB (int4, 300+ tok/s single-stream)
single consumer GPU or Mac
Assumptions (5)
  • BF16 weights (4B params) + 25% KV-cache headroom ≈ 10 GB
  • 1× B200 180GB at $5.98–$14.24/GPU-hour on-demand (2026-09-24)
  • ~15,768 output tok/s aggregate at batch 256 (bandwidth-bound)
  • Blended 3:1 input:output; prefill ~132,891 tok/s
  • Low = 75% utilization at the low GPU price; high = 20% at the high price

Benchmark scores

~ italic, dashed = no published score yet, estimated from related benchmarks.

Coding

SWE-bench Pro (Public)Estimated
~last of 23 (estimated)below measured range (<43.8%)
  1. #1Claude Opus 5.589.9%
  2. #2Claude Sonnet 5.581.3%
  3. #22Nex-N2.5-Mini43.8%
  4. ~#23NVIDIA Nemotron-Labs Dory1.0 4BEstimated<43.8%
No published score — estimated from related benchmarks
AA Coding Agent IndexEstimated
~last of 24 (estimated)below measured range (<26.3)
  1. #1Claude Opus 5.561.7
  2. #2Claude Opus 559.7
  3. #23Muse Spark Open26.3
  4. ~#24NVIDIA Nemotron-Labs Dory1.0 4BEstimated<26.3
No published score — estimated from related benchmarks

Hard reasoning