gpt-oss-120b vs Perceptron Mk1.5 compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Perceptron Mk1.5 — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
| Spec | gpt-oss-120b | Perceptron Mk1.5 | Winner |
|---|---|---|---|
| Maker | OpenAI | Perceptron | – |
| Type | Open-weight | Proprietary | |
| Context window | 131K tokens | 37K tokens | |
| Input price | $0.04/M · free self-host | $0.15/M | |
| Output price | $0.17/M · free self-host | $1.5/M | |
| Vision / multimodal | No | Yes | PEPerceptron Mk1.5 |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | Apache 2.0 | Proprietary |
gpt-oss-120b is ~8.8× cheaper than Perceptron Mk1.5 on output tokens ($0.17 vs $1.5 per M tokens).
| Capability | gpt-oss-120b | Perceptron Mk1.5 |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✗ | ✗ |
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
| Criterion | gpt-oss-120b | Perceptron Mk1.5 |
|---|---|---|
| Cost-efficiency | 5.0 | 4.5 |
| Context window | 3.5 | 2.5 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 3.5 | 5.0 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimize
Perceptron Mk1.5 is Perceptron's embodied reasoning model for physical agents. It accepts text, image, video, and audio input, and answers with text plus optional structured annotations: points, boxes, polygons, tracks,...
These variants are tracked but not compared here — one page per family keeps the comparison readable.
gpt-oss-120b is open-weight and competitive on many tasks, but Perceptron Mk1.5 may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Yes. gpt-oss-120b has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Perceptron Mk1.5 is API-only and cannot be self-hosted.
gpt-oss-120b costs $0.17/M output vs $1.5/M for Perceptron Mk1.5 — roughly 9x cheaper via API, and free if you self-host.
Choose gpt-oss-120b if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Perceptron Mk1.5 if you want frontier capability through a managed API with zero infrastructure to run.
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