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Model Pareto

Phi-4-mini-flash-reasoning

Microsoft AIOpen weightshuggingface.co ↗
Input
—
Output
—
Speed
~58tok/sest.
Context
66Ktokens

3.8B hybrid (SambaY) math-reasoning model. No API price found.

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
~16,098 tok/s
many requests batched
Price
$0.046–0.41 /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 (3.85B params) + 25% KV-cache headroom ≈ 10 GB
  • 1× B200 180GB at $5.98–$14.24/GPU-hour on-demand (2026-09-24)
  • ~16,098 output tok/s aggregate at batch 256 (bandwidth-bound)
  • Blended 3:1 input:output; prefill ~138,068 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.