> ## Documentation Index
> Fetch the complete documentation index at: https://docs.apiyi.com/llms.txt
> Use this file to discover all available pages before exploring further.

# GPT-5.5 Launch: OpenAI's Newest Frontier Model with xhigh Reasoning Tier

> OpenAI launched GPT-5.5 on April 23, 2026, just six weeks after GPT-5.4. SWE-bench Verified 88.7%, 60% fewer hallucinations, and a new xhigh reasoning tier. APIYI's official direct-relay channel is live at identical official pricing: $5 input / $30 output per million tokens.

## Key Highlights

* **Newest frontier model**: OpenAI's flagship for the most complex professional work, just 6 weeks after GPT-5.4
* **xhigh reasoning tier**: `reasoning.effort` adds `xhigh`, bringing the lineup to none / low / medium (default) / high / xhigh
* **Million-token context**: 1,050,000 input window, 128,000 max output tokens
* **Official direct-relay channel**: APIYI relays OpenAI's official endpoint — same model, same behavior
* **Pricing matches the official rate**: \$5 / 1M input, \$30 / 1M output, with cached input at just \$0.50

## Background

On April 23, 2026, OpenAI released GPT-5.5, positioned as "our newest frontier model for the most complex professional work." It arrives only six weeks after GPT-5.4, continuing OpenAI's accelerated release cadence.

Compared to GPT-5.4 (\$2.50 input / \$15 output for the standard tier), GPT-5.5 doubles the per-token price. OpenAI's argument: the new model is materially more token-efficient on hard tasks, so independent benchmarks put the net intelligence-cost increase at roughly 20%. In practice — **higher per-token price, but fewer tokens burned per task**.

The GPT-5.5 family ships in three variants: standard `gpt-5.5`, `gpt-5.5 Thinking` (extended reasoning budget), and `gpt-5.5 Pro` (highest accuracy, available only on Pro/Business/Enterprise plans). APIYI's first launch is the **standard `gpt-5.5` over OpenAI's official direct-relay channel** — no rerouting, no degradation, identical weights, behavior, and rate limits.

## Detailed Analysis

### Core Features

<CardGroup cols={2}>
  <Card title="xhigh reasoning tier" icon="brain">
    `reasoning.effort` adds `xhigh`, designed for the hardest multi-step reasoning and coding tasks
  </Card>

  <Card title="Coding leap" icon="code">
    SWE-bench Verified hits 88.7%, a new OpenAI internal record
  </Card>

  <Card title="Far fewer hallucinations" icon="shield-check">
    \~60% reduction vs. GPT-5.4, much more reliable for professional output
  </Card>

  <Card title="Million-token context" icon="book-open">
    1.05M input + 128K output — fits an entire codebase or several long documents
  </Card>
</CardGroup>

### `reasoning.effort` — five tiers explained

GPT-5.5 is the only OpenAI model on APIYI today supporting all five reasoning tiers:

| Tier               | Use case                           | Notes                                   |
| ------------------ | ---------------------------------- | --------------------------------------- |
| `none`             | Instant replies, simple Q\&A       | No reasoning tokens — fastest, cheapest |
| `low`              | Casual chat, lightweight tasks     | Minimal reasoning, balanced             |
| `medium` (default) | General purpose                    | The default; covers most workloads      |
| `high`             | Complex analysis, long chains      | Significantly larger reasoning budget   |
| `xhigh`            | Hardest coding, research, planning | Top-tier reasoning budget — new in 5.5  |

<Info>
  `xhigh` materially increases reasoning-token consumption. Validate at `medium` / `high` first and only escalate to `xhigh` when the task genuinely needs it.
</Info>

### Performance Highlights

| Benchmark              | GPT-5.5               | GPT-5.4  | Delta                         |
| ---------------------- | --------------------- | -------- | ----------------------------- |
| **SWE-bench Verified** | **88.7%**             | \~85%    | +3.7pp                        |
| **Hallucination rate** | **−60%**              | baseline | Major improvement             |
| **Token efficiency**   | Fewer tokens per task | baseline | Offsets \~half the price hike |

<Info>
  Source: OpenAI's official model card and the Microsoft Azure Foundry announcement (April 23, 2026). Benchmark numbers can vary with evaluation conditions.
</Info>

### Technical Specs

| Parameter            | GPT-5.5                                 |
| -------------------- | --------------------------------------- |
| **Model name**       | `gpt-5.5`                               |
| **Snapshot**         | `gpt-5.5-2026-04-23`                    |
| **Context window**   | 1,050,000 tokens                        |
| **Max output**       | 128,000 tokens                          |
| **Knowledge cutoff** | Dec 1, 2025                             |
| **Reasoning tokens** | Supported                               |
| **reasoning.effort** | none / low / medium / high / xhigh      |
| **API endpoints**    | `/v1/chat/completions`, `/v1/responses` |

## Practical Use

### Recommended scenarios

GPT-5.5's higher unit price means it's **not a default for everyday chat**. It earns its keep on:

1. **Complex code engineering**: large refactors, cross-file bug hunts, SWE-bench-style multi-step work
2. **Professional research**: legal, financial, medical, or scientific work where rigorous reasoning and low hallucinations matter
3. **Long-context analysis**: million-token codebase audits, cross-document comparison
4. **Autonomous agents**: multi-step planning workflows that need self-correction
5. **xhigh reasoning tasks**: problems other models simply can't solve, justifying the top reasoning budget

### Code Examples

#### Standard call (default `medium` reasoning)

```python theme={null}
from openai import OpenAI

client = OpenAI(
    api_key="your-apiyi-key",
    base_url="https://api.apiyi.com/v1"
)

response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[
        {"role": "user", "content": "Refactor this Python code and explain your design decisions..."}
    ],
    max_tokens=8192
)

print(response.choices[0].message.content)
```

#### Using the `xhigh` reasoning tier

```python theme={null}
response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[
        {"role": "user", "content": "Here's a complex distributed-system deadlock. Give root cause and a fix..."}
    ],
    reasoning_effort="xhigh",
    max_tokens=16384
)

print(response.choices[0].message.content)
```

#### Save cost by skipping reasoning (`none`)

```python theme={null}
response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[
        {"role": "user", "content": "Translate this Chinese paragraph to English"}
    ],
    reasoning_effort="none",
    max_tokens=2048
)

print(response.choices[0].message.content)
```

### Best Practices

1. **Match tier to difficulty**: use `none` / `low` for simple tasks; only escalate to `xhigh` for genuinely hard ones
2. **Use cached input**: cached input drops to \$0.50 / 1M — 1/10th of the standard rate
3. **Be careful combining long context with `xhigh`**: a million-token prompt at `xhigh` reasoning can be expensive — confirm you need both
4. **Not every task needs GPT-5.5**: chat, translation, and summarization are usually better served by GPT-5.4 or earlier

## Pricing & Availability

### Pricing (matches OpenAI's official rate)

| Item             | Rate                | Notes                       |
| ---------------- | ------------------- | --------------------------- |
| **Input**        | \$5.00 / 1M tokens  | Standard input              |
| **Cached input** | \$0.50 / 1M tokens  | On cache hit — 90% discount |
| **Output**       | \$30.00 / 1M tokens | Includes reasoning tokens   |

### Comparison with recent models

| Model           | Input      | Output      | Position                           |
| --------------- | ---------- | ----------- | ---------------------------------- |
| **GPT-5.5**     | **\$5.00** | **\$30.00** | Newest frontier, xhigh reasoning   |
| GPT-5.4         | \$2.50     | \$15.00     | Prior flagship, still strong value |
| Claude Opus 4.7 | \$5.00     | \$25.00     | Coding flagship                    |
| Gemini 3 Pro    | \$2.00     | \$12.00     | Multimodal                         |

<Warning>
  GPT-5.5 is 2× the price of GPT-5.4. If GPT-5.4 already handles your task, **don't blindly upgrade**. GPT-5.5's value lives in `xhigh` reasoning and the hardest tasks.
</Warning>

### Stack with deposit promotions

<Card title="Latest deposit promotions" icon="gift" href="/en/faq/recharge-promotions">
  APIYI offers deposit bonuses on top of official-rate pricing — bonuses effectively reduce per-call cost.
</Card>

### Available Models

| Model name           | Channel                      | Notes                                     |
| -------------------- | ---------------------------- | ----------------------------------------- |
| `gpt-5.5`            | OpenAI official direct-relay | Latest, auto-tracks the official snapshot |
| `gpt-5.5-2026-04-23` | OpenAI official direct-relay | Pinned snapshot                           |

### Access

* Site: `apiyi.com`
* API endpoint: `https://api.apiyi.com/v1`
* OpenAI-compatible — just swap `base_url` and `api_key`

## Summary & Recommendation

GPT-5.5 is OpenAI's strongest, and most expensive, general model right now. Its value comes from two things: the **`xhigh` reasoning tier** and the **substantially lower hallucination rate**.

**Worth upgrading if you**:

* Already use GPT-5.4 and still hit reasoning ceilings on hard tasks
* Work in hallucination-sensitive domains (legal, finance, medical, research)
* Have multi-step coding or planning tasks that need `xhigh` to land

**Not worth upgrading if you**:

* Run general chat, translation, or summarization (older models are cheaper and good enough)
* Run high-volume calls where per-call cost matters
* Already have GPT-5.4 at `medium` reasoning solving the task reliably

APIYI now serves GPT-5.5 over the **official direct-relay channel** — identical behavior to OpenAI's own endpoint, at identical pricing. We recommend running a small A/B against GPT-5.4 on your real workload before switching wholesale.

<Info>
  Sources: OpenAI official model card (developers.openai.com), Microsoft Azure Foundry announcement, independent benchmark coverage. Data retrieved: April 25, 2026.
</Info>