Phi-3 Medium vs Claude 3.5 Sonnet
Head-to-head specifications
| Metric | Phi-3 Medium | Claude 3.5 Sonnet | Difference |
|---|---|---|---|
| MMLU (general capability) | 78.0% | 88.7% | -10.7% |
| Context window | 128K tokens | 200K tokens | — |
| Price (input / output per 1M) | Open weights | $3 / $15 | — |
| Access | Open weights | Proprietary API | — |
- Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 78.0%).
- Claude 3.5 Sonnet offers the larger context window, useful for long documents and codebases.
Verdict: Phi-3 Medium or Claude 3.5 Sonnet?
Phi-3 Medium advantages
- No decisive advantage on the tracked metrics.
Claude 3.5 Sonnet advantages
- General capability (+12%)
- Context window (+36%)
Which should you choose?
- Choose the Claude 3.5 Sonnet if you need the strongest reasoning and accuracy.
Value for money
Phi-3 Medium is open-weight and can be self-hosted, which can dramatically lower cost at scale versus a per-token API.
Phi-3 Medium vs Claude 3.5 Sonnet: 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.
Claude 3.5 Sonnet — Anthropic large language model (2024) with a 200K-token context window and an MMLU score of 88.7%.
Phi-3 Medium vs Claude 3.5 Sonnet: Claude 3.5 Sonnet scores higher on the MMLU benchmark. Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 78.0%). Claude 3.5 Sonnet offers the larger context window, useful for long documents and codebases.
Capability and reasoning
On MMLU — a 57-subject benchmark of general knowledge and reasoning — the Claude 3.5 Sonnet 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 Claude 3.5 Sonnet handles up to 200K 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 Claude 3.5 Sonnet 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.
Frequently asked questions
Is the Phi-3 Medium better than the Claude 3.5 Sonnet?
Claude 3.5 Sonnet is the clearly stronger overall choice, winning most of the dimensions that matter. Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 78.0%).
What is the main difference between the Phi-3 Medium and the Claude 3.5 Sonnet?
Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 78.0%). Claude 3.5 Sonnet offers the larger context window, useful for long documents and codebases.
Which is better value?
Phi-3 Medium is open-weight and can be self-hosted, which can dramatically lower cost at scale versus a per-token API.
Which should I choose?
Choose the Claude 3.5 Sonnet if you need the strongest reasoning and accuracy.
Methodology
Large language models are compared on the MMLU benchmark (a widely-cited 57-subject test of general knowledge and reasoning, reported as a percentage), maximum context window, and published API pricing per million input and output tokens. Open-weight models can also be self-hosted. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit.