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Model Pareto

Nemotron 3.5 Super VL

NVIDIAOpen weightshuggingface.co ↗
Input
—
Output
—
Speed
~160tok/sest.
Context
1Mtokens
Price
—
Time
—

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
2× B200 180GB
FP8 weights
Throughput
~12,551 tok/s
many requests batched
Price
$0.11–0.96 /M tok
busy → light use
On your own machine
Mac Studio M5 Max 128GB (int4, ~72 tok/s single-stream)
single consumer GPU or Mac
Assumptions (5)
  • FP8 weights (120B params, 12B active per token) + 40% KV-cache headroom ≈ 168 GB
  • 2× B200 180GB at $5.98–$14.24/GPU-hour on-demand (2026-09-24)
  • ~12,551 output tok/s aggregate at batch 359 (bandwidth-bound); MoE compute scales with active params
  • Blended 3:1 input:output; prefill ~177,188 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

Writing & chat

Vision

Hard reasoning

Agents

OSWorld 2.0Estimated
~last of 5 (estimated)below measured range (<47.5%)
  1. #1GLM-5.3 Flash59.1%
  2. #2Kimi K358.3%
  3. #4GPT-5.547.5%
  4. ~#5Nemotron 3.5 Super VLEstimated<47.5%
No published score — estimated from related benchmarks
~#28 of 91 (estimated)~1417 Elo
  1. #1Claude Opus 5.51866
  2. #2Muse Wonder Full1857
  3. #27Qwen3.8 27B1419
  4. ~#28Nemotron 3.5 Super VLEstimated1417
  5. #28K2 Horizon 375B A23B1361
No published score — estimated from related benchmarks
~#33 of 84 (estimated)~26.9%
  1. #1Muse Wonder Full71.3%
  2. #2Claude Opus 5.569.5%
  3. #32Apodex 1.128.2%
  4. ~#33Nemotron 3.5 Super VLEstimated26.9%
  5. #33GPT-5.4 mini26.2%
No published score — estimated from related benchmarks
~#32 of 91 (estimated)~22.9%
  1. #1Muse Spark 1.350.5%
  2. #2GLM-5.350.3%
  3. #31Hy322.9%
  4. ~#32Nemotron 3.5 Super VLEstimated22.9%
  5. #32K2-Horizon-32B22.5%
No published score — estimated from related benchmarks