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Model Pareto

K2 Horizon 3.7B

MBZUAI Institute of Foundation ModelsOpen weightsartificialanalysis.ai ↗
Input
—
Output
—
Speed
~110tok/sest.
Context
524Ktokens

Long-tail import from Artificial Analysis (2026-09-24); AA variant: K2 Horizon 3.7B. Price = AA median host price.

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
~13,869 tok/s
many requests batched
Price
$0.056–0.50 /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 (5.06B params) + 40% KV-cache headroom ≈ 14 GB
  • 1× B200 180GB at $5.98–$14.24/GPU-hour on-demand (2026-09-24)
  • ~13,869 output tok/s aggregate at batch 256 (bandwidth-bound)
  • Blended 3:1 input:output; prefill ~105,052 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

~#18 of 19 (estimated)~47.1%
  1. #1Claude Opus 5.589.9%
  2. #2Claude Sonnet 5.581.3%
  3. #17Muse Glimmer51.2%
  4. ~#18K2 Horizon 3.7BEstimated47.1%
  5. #18Nex-N2.5-Mini43.8%
No published score — estimated from related benchmarks
DeepSWE v1.1Estimated
~#29 of 31 (estimated)~37.9%
  1. #1DeepSeek V4.1 Flash74.2%
  2. #2Grok 4.772.6%
  3. #28Qwen3.8 27B42.2%
  4. ~#29K2 Horizon 3.7BEstimated37.9%
  5. #29Nex-N2.5-Mini36.1%
No published score — estimated from related benchmarks
LiveCodeBenchEstimated
~#14 of 20 (estimated)~42.7%
  1. #1Qwen3.8-Omni-Flash92.6%
  2. #2Qwen3.8 Flash-Next91.9%
  3. #13Devstral 244.8%
  4. ~#14K2 Horizon 3.7BEstimated42.7%
  5. #14Llama 4 Maverick39.7%
No published score — estimated from related benchmarks
~last of 15 (estimated)below measured range (<41.1)
  1. #1Claude Opus 5.566.0
  2. #2Claude Fable 5.162.2
  3. #14GPT-6 Luna41.1
  4. ~#15K2 Horizon 3.7BEstimated<41.1
No published score — estimated from related benchmarks

Hard reasoning

Agents