Phi-3 Medium vs GPT-4o

Phi-3 Medium vs GPT-4o: which should you choose?

Phi-3 Medium — Microsoft large language model (2024) with a 128K-token context window and an MMLU score of 78.0%, released with open weights.

GPT-4o — OpenAI large language model (2024) with a 128K-token context window and an MMLU score of 88.7%.

Phi-3 Medium vs GPT-4o: GPT-4o scores higher on the MMLU benchmark. GPT-4o leads general capability (MMLU 88.7% vs 78.0%).

Capability and reasoning

On MMLU — a 57-subject benchmark of general knowledge and reasoning — the GPT-4o scores 88.7% versus 78.0%. MMLU is a useful proxy for raw knowledge but does not capture instruction-following, coding, tool use, latency or safety, so treat it as one signal among several.

Context window

The Phi-3 Medium handles up to 128K tokens per request, which sets how much documentation, transcript or code it can reason over at once — decisive for retrieval-augmented and long-document workflows.

Pricing and access

Phi-3 Medium is open weights and GPT-4o is proprietary api. Proprietary models bill per token via API; open-weight models can be self-hosted, trading per-call cost for infrastructure you manage. For production, weigh throughput, rate limits and data-residency needs alongside headline price.

The verdict

Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.