GPT-5.5 vs Phi-3 Mini 4k
GPT-5.5 (2026) and Phi-3 Mini 4k (2024) are frontier reasoning models from OpenAI and Microsoft Research. GPT-5.5 ships a 1.05m-token context window, while Phi-3 Mini 4k ships a 4k-token context window. On MMLU PRO, GPT-5.5 leads by 42.4 pts. On pricing, GPT-5.5 ranges from $5 to $8/1M input tokens by tier; Phi-3 Mini 4k costs $0.05/1M input tokens. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5.5 fits 263x more tokens; pick it for long-context work and Phi-3 Mini 4k for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-5.5 | Phi-3 Mini 4k |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding and Classification |
| Context window | 1.05m | 4k |
| Cheapest output | $30/1M tokens | $0.25/1M tokens |
| Provider routes | 3 tracked | 4 tracked |
| Shared benchmarks | MMLU PRO leader | 5 rows |
Decision tradeoffs
- GPT-5.5 holds a shared-benchmark lead on MMLU PRO, ahead by 42.4 points.
- GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.5 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags GPT-5.5 for Coding, RAG, and Agents.
- Phi-3 Mini 4k has the lower cheapest tracked output price at $0.25/1M tokens.
- Phi-3 Mini 4k has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Phi-3 Mini 4k for Coding and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.5
$11,500
Cheapest tracked route/tier: OpenAI API 0-272K input tokens
Phi-3 Mini 4k
$103
Cheapest tracked route/tier: Replicate API
Estimated monthly gap: $11,398. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.5 and Phi-3 Mini 4k; plan for SDK, billing, or endpoint changes.
- Phi-3 Mini 4k is $29.75/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- No overlapping tracked provider route is sourced for Phi-3 Mini 4k and GPT-5.5; plan for SDK, billing, or endpoint changes.
- GPT-5.5 is $29.75/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-23 | 2024-04-23 |
| Context window | 1.05m | 4k |
| Parameters | — | 3.8B |
| Architecture | decoder only | decoder only |
| License | Proprietary | MIT(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-12 | 2023-10 |
Pricing and availability
| Pricing attribute | GPT-5.5 | Phi-3 Mini 4k |
|---|---|---|
| Input price |
| $0.05/1M tokens |
| Output price |
| $0.25/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.5 | Phi-3 Mini 4k |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GPT-5.5 | Phi-3 Mini 4k |
|---|---|---|
| MMLU PRO | 88.1 | 45.7 |
| Google-Proof Q&A | 93.6 | 40.9 |
| HumanEval | 94.2 | 59.8 |
| Instruction-Following Evaluation | 92.1 | 45.0 |
| Massive Multitask Language Understanding | 92.4 | 68.2 |
Deep dive
On shared benchmark coverage, MMLU PRO has GPT-5.5 at 88.1 and Phi-3 Mini 4k at 45.7, with GPT-5.5 ahead by 42.4 points; Google-Proof Q&A has GPT-5.5 at 93.6 and Phi-3 Mini 4k at 40.9, with GPT-5.5 ahead by 52.7 points; HumanEval has GPT-5.5 at 94.2 and Phi-3 Mini 4k at 59.8, with GPT-5.5 ahead by 34.4 points. The largest visible gap is 52.7 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: GPT-5.5, multimodal input: GPT-5.5, reasoning mode: GPT-5.5, function calling: GPT-5.5, tool use: GPT-5.5, structured outputs: GPT-5.5, and code execution: GPT-5.5. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output, while Phi-3 Mini 4k lists $0.05/1M input and $0.25/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-3 Mini 4k lower by about $12.39 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 3 providers versus 4, so concentration risk also matters.
Choose GPT-5.5 when coding workflow support and larger context windows are central to the workload. Choose Phi-3 Mini 4k when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-5.5 or Phi-3 Mini 4k?
GPT-5.5 supports 1.05m tokens, while Phi-3 Mini 4k supports 4k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GPT-5.5 or Phi-3 Mini 4k?
GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output. Phi-3 Mini 4k lists $0.05/1M input and $0.25/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.5 or Phi-3 Mini 4k open source?
GPT-5.5 is listed under Proprietary. Phi-3 Mini 4k is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.5 or Phi-3 Mini 4k?
GPT-5.5 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-5.5 or Phi-3 Mini 4k?
GPT-5.5 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.5 and Phi-3 Mini 4k?
GPT-5.5 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Phi-3 Mini 4k is available on Microsoft Foundry, NVIDIA NIM, Baseten API, and Replicate API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-08. Data sourced from public model cards and provider documentation.