GPT-5.5 vs GPT-5.4 for Translation
Compare GPT-5.5 by OpenAI and GPT-5.4 by OpenAI for translation tasks - pricing, context windows, and strengths, and see how to put either to work in Appaca.
GPT-5.5
OpenAI's smartest and most capable model yet for agentic coding, knowledge work, and computer use, delivering a new class of intelligence at GPT-5.4 latency.
View GPT-5.5GPT-5.4
OpenAI's frontier model for complex professional work with best intelligence at scale for agentic, coding, and professional workflows.
View GPT-5.4GPT-5.5 vs GPT-5.4 at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.5 | GPT-5.4 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Text |
| Context window | 1M tokens | 1.05M tokens |
| Input price | $5 / 1M tokens | $2.5 / 1M tokens |
| Output price | $30 / 1M tokens | $15 / 1M tokens |
| Status | Current | Current |
What matters for Translation
Evaluation criteria and how GPT-5.5 and GPT-5.4 compare on what translation tasks actually require.
Translation accuracy and cultural appropriateness
Support for low-resource and regional languages
Domain-specific terminology handling
Consistency across large documents
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GPT-5.4 is 50% cheaper on input tokens ($2.5 vs $5 per million), which adds up quickly on high-volume translation workloads.
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GPT-5.4 is 50% cheaper on output tokens ($15 vs $30 per million) - the bigger factor for translation tasks that generate long responses.
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Context windows are close: GPT-5.5 handles 1M tokens and GPT-5.4 handles 1.05M tokens.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-5.5
1. Strongest Agentic Coding Model
- State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
- Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.
2. Higher Intelligence at GPT-5.4 Latency
- Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
- Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.
3. Powerful for Knowledge Work & Computer Use
- Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
- Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.
4. Scientific Research Co-Scientist
- Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
- Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.
GPT-5.4
1. Best Intelligence at Scale
- OpenAI positions GPT-5.4 as its frontier model for agentic, coding, and professional workflows.
- Built for complex professional work where stronger reasoning and higher answer quality matter.
2. Configurable Reasoning + Multimodal Input
- Supports configurable reasoning effort from none to xhigh, letting teams balance speed and depth.
- Accepts both text and image inputs while producing text output.
3. Massive Context for Long-Running Work
- 1.05M token context window supports very large codebases, documents, and multi-step workflows.
- Allows up to 128 k output tokens for long-form answers and larger generations.
4. Updated Knowledge & Broad Tool Support
- Knowledge cut-off of Aug 31 2025 keeps it current for newer frameworks and business context.
- Supports tools like web search, file search, code interpreter, hosted shell, computer use, and MCP in the Responses API.
Use GPT-5.5 or GPT-5.4 - or both
Appaca is the AI workspace for operators. Build internal translation tools and AI co-workers powered by GPT-5.5 or GPT-5.4 - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need for translation and it builds a working app powered by GPT-5.5 or GPT-5.4. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.5, test the same tool on GPT-5.4, and keep whichever performs better for your translation workflow - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs for translation and it builds a working app powered by GPT-5.5 or GPT-5.4 - connected to the tools you already use.
Keep comparing for Translation
More side-by-side model comparisons for translation tasks.
FAQs
GPT-5.4 and Gemini 2.5 Pro are the top translation LLMs in 2026. GPT-5.4 produces the most natural translations for major European and East Asian languages, with strong idiom handling. Gemini 2.5 Pro excels at lower-resource languages and multilingual tasks. Claude 4 Sonnet is a strong choice when tone and register consistency across a long document is the priority.
GPT-5.4 is generally cheaper: $2.5 input / $15 output per million tokens, versus $5 / $30 for GPT-5.5. Actual cost depends on how many tokens your translation workload reads and writes.
GPT-5.4 has the larger context window at 1.05M tokens, compared to 1M tokens for GPT-5.5. For translation tasks, a larger window means the model can consider more context at once without losing track.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs for translation and the Appaca agent builds it as a working app powered by GPT-5.5, GPT-5.4, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build Translation tools with GPT-5.5 or GPT-5.4
Describe the translation tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.