Phi-4 Reasoning vs gpt-oss-120b
At a Glance
| Compare |  Phi-4 ReasoningMicrosoft |  gpt-oss-120bOpenAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v4.4 | UnrankedNot in the 57-model eligible cohort | #43 of 570.0 score · 1/3 sources · single-source provisional · missing LiveBench, ARC-AGI-2 · full-core range 0.0–66.7 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.0296Openrouter ↗ · Oct 19, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.136Openrouter ↗ · Oct 19, 2026 |
| Context windowMaximum documented tokens | 33K | 131K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Phi-4-reasoning | gpt-oss-120b |
|---|---|---|
| Developer | Microsoft | OpenAI |
| Family | Phi 4 Reasoning | Gpt Oss 120b |
| Model | Phi-4-reasoning | gpt-oss-120b |
| Version | Phi-4-reasoning | gpt-oss-120b |
| Lifecycle | active | active |
| Released | 2025-04-30 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 33K | 131K |
| Total parameters | 14.7B | 116.8B |
| Active parameters | Unknown | 5.1B |
| License | mit | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Unknown | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Cerebras (Standard), Deepinfra (Standard), Fireworks Ai (Serverless, Standard), Groq (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Serverless, Standard) |
| Capabilities | chat, generation, reasoning | chat, generation, reasoning, tools |
Phi-4 Reasoning Capabilities
gpt-oss-120b Capabilities
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Primary Evidence
Sources and Freshness
Questions
Phi-4 Reasoning vs gpt-oss-120b FAQs
Is Phi-4 Reasoning or gpt-oss-120b better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Phi-4 Reasoning and gpt-oss-120b, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Phi-4 Reasoning or gpt-oss-120b?+
Only gpt-oss-120b has a directly sourced input price: $0.0296 per million tokens. Only gpt-oss-120b has a directly sourced output price: $0.136 per million tokens.
Which has a larger context window, Phi-4 Reasoning or gpt-oss-120b?+
gpt-oss-120b has the larger sourced context window. Phi-4 Reasoning supports 32,768 tokens and gpt-oss-120b supports 131,072 tokens.
Which performs better in benchmarks, Phi-4 Reasoning or gpt-oss-120b?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Phi-4 Reasoning or gpt-oss-120b be self-hosted?+
Both models have the same sourced self-hosting status: supported. Phi-4 Reasoning is open weight; gpt-oss-120b is open weight.
Can Phi-4 Reasoning and gpt-oss-120b understand images?+
Phi-4 Reasoning is not documented with image input; gpt-oss-120b is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Phi-4 Reasoning or gpt-oss-120b?+
Neither model has a sourced maximum output in this comparison, so a larger limit cannot be determined.
Do Phi-4 Reasoning and gpt-oss-120b support reasoning and tool use?+
Phi-4 Reasoning: reasoning. gpt-oss-120b: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Phi-4 Reasoning or gpt-oss-120b?+
Phi-4 Reasoning has 0 sourced provider routes; gpt-oss-120b has 7, so gpt-oss-120b has broader tracked availability.
Which offers better value, Phi-4 Reasoning or gpt-oss-120b?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.