Claude Sonnet 4.6 vs Phi-4 Reasoning
Model Markets Rankings
Intelligence, Cost, and Efficiency
| Ranking | Claude Sonnet 4.6 | Phi-4-reasoning |
|---|---|---|
| IntelligenceHigher is better · MM Intelligence v1.4 | #25 of 4660.3 score · 3/3-source complete | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #32 of 45$0.198 per LiveBench case | UnrankedNot in the 45-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.1 | #31 of 3846.0 score · 3/3-source intelligence | UnrankedNot in the 38-model eligible cohort |
Ranks come from current available eligible cohorts. Intelligence may use a labeled two-of-three partial core. Green highlights appear only when both models are ranked in the same metric, and the three dimensions are not collapsed into an overall winner.
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Claude Sonnet 4.6 | Phi-4-reasoning |
|---|---|---|
| Developer | Anthropic | Microsoft |
| Family | Claude 4 | Phi 4 Reasoning |
| Model | Claude Sonnet 4.6 | Phi-4-reasoning |
| Version | Claude Sonnet 4.6 | Phi-4-reasoning |
| Lifecycle | active | active |
| Released | 2026-02-17 | 2025-04-30 |
| Knowledge cutoff | 2025-08-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 33K |
| Total parameters | Unknown | 14.7B |
| Active parameters | Unknown | Unknown |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | Unknown |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard), Deepinfra (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning |
12 comparable fields · 10 material differences · Pair passes the primary-source comparison gate
Claude Sonnet 4.6 Capabilities
Phi-4 Reasoning Capabilities
Internal Comparison Graph
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Primary Evidence
Sources and Freshness
Questions
Claude Sonnet 4.6 vs Phi-4 Reasoning FAQs
Is Claude Sonnet 4.6 or Phi-4 Reasoning better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Sonnet 4.6 and Phi-4 Reasoning, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Sonnet 4.6 or Phi-4 Reasoning?+
Only Claude Sonnet 4.6 has a directly sourced input price: $3.00 per million tokens. Only Claude Sonnet 4.6 has a directly sourced output price: $15.00 per million tokens.
Which has a larger context window, Claude Sonnet 4.6 or Phi-4 Reasoning?+
Claude Sonnet 4.6 has the larger sourced context window. Claude Sonnet 4.6 supports 1,000K and Phi-4 Reasoning supports 33K.
Which performs better in benchmarks, Claude Sonnet 4.6 or Phi-4 Reasoning?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Sonnet 4.6 or Phi-4 Reasoning be self-hosted?+
Phi-4 Reasoning is the only model in this pair currently marked as self-hostable. Claude Sonnet 4.6 is not marked open weight; Phi-4 Reasoning is open weight.
Can Claude Sonnet 4.6 and Phi-4 Reasoning understand images?+
Claude Sonnet 4.6 is documented with image input; Phi-4 Reasoning is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Sonnet 4.6 or Phi-4 Reasoning?+
Neither has a larger sourced maximum output. Claude Sonnet 4.6 is 128K and Phi-4 Reasoning is —.
Do Claude Sonnet 4.6 and Phi-4 Reasoning support reasoning and tool use?+
Claude Sonnet 4.6: reasoning, tool calling, and image input. Phi-4 Reasoning: reasoning. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Sonnet 4.6 or Phi-4 Reasoning?+
Claude Sonnet 4.6 has 2 sourced provider routes; Phi-4 Reasoning has 0, so Claude Sonnet 4.6 has broader tracked availability.
Which offers better value, Claude Sonnet 4.6 or Phi-4 Reasoning?+
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.