LANGUAGE MODEL OpenAI Last updated:

GPT-5.3 Instant NEW

Better Everyday Chat (Less “Caveats”)

GPT-5.3 Instant was an iteration aimed less at benchmark leaps and more at the “feel” of ChatGPT: fewer preachy disclaimers, fewer unnecessary refusals, and more direct answers when a request is safe. It’s a reminder that product quality in LLMs often comes from judgment, tone, and retrieval synthesis—not only raw capability scores.

Intelligence
Top 1%
Speed
Medium
96 tok/s output
Cost
High
$5.00 in / $30.00 out
Context
922K
Up to 922,000 tokens
How are Intelligence, Speed & Cost bucketed?
Intelligence and Speed buckets are percentile ranks on Artificial Analysis. Cost buckets are fixed dollar thresholds keyed off output-token price ($/M out).
Intelligence
  • Top 1%≤ 1%
  • Top 5%≤ 5%
  • Top 10%≤ 10%
  • Good≤ 25%
  • Medium≤ 50%
  • Below avg> 50%
Speed
  • Top 1%≥ 345 tok/s
  • Top 5%≥ 237 tok/s
  • Top 10%≥ 196 tok/s
  • Good≥ 146 tok/s
  • Medium≥ 90 tok/s
  • Slow< 90 tok/s
Cost
  • Freeopen weights · self-host
  • Low< $1 / M out
  • Moderate$1–5 / M out
  • High≥ $5 / M out

Why it matters

It shows “generation” isn’t only bigger models—sometimes it’s a better default behavior that users notice immediately.

Core Capabilities

Long Documents
Handles entire codebases, books, and multi-doc RAG.
Generative
Produces images, video, audio, or other media.
Reasoning
Solves complex math, logic, and planning tasks.

Context Window

922k tokens
≈ 709+ pages
4k Chat 聊天
32k Long docs 长文档
128k Books 整本书
400k Multi-doc 多文档
1M This model 本模型
10M

Availability

API
Not available
Product / App
Available
Open Source
Not released
Enterprise
Contact sales

Pricing Model

Subscription
Bundled inside the host product.
Subscription

Capability / Performance

Where this model sits relative to the middle 60% of models in the tree. All scores are 0–10 (higher is better).

Lower 20% Upper 80% This model
Reasoning
AA Intelligence Index · scaled to 10
1.7
5.6
6.0
Coding
SciCode · scaled to 10
1.8
4.3
5.7
Agentic tasks
Terminal-Bench Hard · scaled to 10
0.2
3.6
6.1
Context / memory
Context window size · log-scaled
6.0
9.0
8.9
Cost efficiency
Input price ($/M tokens) · cheaper scores higher
6.2
10.0
3.8
Lower 20% 20th percentile — 20% of models score below this This model Where the current model lands Upper 80% 80th percentile — only 20% of models score above this Percentile boundaries are computed across every model in the tree that reports the underlying benchmark for each capability.

What it feels like

  • Mid-cycle GPT-5 refresh between 5.2 and 5.5.
  • Pro variant hits 93.2% on GPQA Diamond and 40.3% on FrontierMath Tier 1-3 — new state-of-the-art on hard math/science
  • 400K-token context window — biggest OpenAI window yet, designed for long-running agents
  • GDPval state-of-the-art — outperforms industry professionals on well-specified tasks across 44 occupations

Best use cases

  • Hardest math/science research where Pro/Thinking modes pull ahead of every competitor
  • Long-running professional agent workflows (400K context + GDPval-leading task quality)
  • Knowledge work spanning 44 occupations — spreadsheets, presentations, multi-step projects

Tools to try

Not ideal for

  • Casual chat or creative writing — Instant tier feels muted compared to GPT-5.1
  • Cost-sensitive bulk inference — 40% price hike vs 5.1 with no automatic upgrade win

Model Evolution

GPT is OpenAI's language model family.

View full evolution tree →