| Signal | GPT-5.1-Codex-Max | Delta | GPT-5.4 Nano |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 88 | -2 | |
Pricing | 90 | -9 | |
Context window size | 89 | -- | |
Recency | 100 | -- | |
Output Capacity | 85 | -- | |
| Overall Result | 0 wins | of 6 | 2 wins |
Score History
87.8
current score
GPT-5.1-Codex-Max
right now
79.3
current score
OpenAI
OpenAI
GPT-5.4 Nano saves you $542.50/month
That's $6510.00/year compared to GPT-5.1-Codex-Max at your current usage level of 100K calls/month.
| Metric | GPT-5.1-Codex-Max | GPT-5.4 Nano | Winner |
|---|---|---|---|
| Overall Score | 88 | 79 | GPT-5.1-Codex-Max |
| Rank | #14 | #42 | GPT-5.1-Codex-Max |
| Quality Rank | #14 | #42 | GPT-5.1-Codex-Max |
| Adoption Rank | #14 | #42 | GPT-5.1-Codex-Max |
| Parameters | -- | -- | -- |
| Context Window | 400K | 400K | -- |
| Pricing | $1.25/$10.00/M | $0.20/$1.25/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | GPT-5.1-Codex-Max |
| Benchmarks | 88 | 90 | GPT-5.4 Nano |
| Pricing | 90 | 99 | GPT-5.4 Nano |
| Context window size | 89 | 89 | GPT-5.1-Codex-Max |
| Recency | 100 | 100 | GPT-5.1-Codex-Max |
| Output Capacity | 85 | 85 | GPT-5.1-Codex-Max |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 88/100 (rank #14), placing it in the top 96% of all 290 models tracked.
Scores 79/100 (rank #42), placing it in the top 86% of all 290 models tracked.
GPT-5.1-Codex-Max has a 9-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
GPT-5.4 Nano offers 87% better value per quality point. At 1M tokens/day, you'd spend $21.75/month with GPT-5.4 Nano vs $168.75/month with GPT-5.1-Codex-Max - a $147.00 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. GPT-5.4 Nano also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.25/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (88/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-5.1-Codex-Max has a moderate advantage with a 8.5-point lead in composite score. It wins on more signal dimensions, but GPT-5.4 Nano has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-5.1-Codex-Max
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5.4 Nano
87% lower pricing; better value at scale
Best for Reliability
GPT-5.1-Codex-Max
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.1-Codex-Max
Stronger community support and better developer experience
Best for Production
GPT-5.1-Codex-Max
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.1-Codex-Max | GPT-5.4 Nano |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
OpenAI
GPT-5.4 Nano saves you $12.39/month
That's 87% cheaper than GPT-5.1-Codex-Max at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-5.1-Codex-Max | GPT-5.4 Nano |
|---|---|---|
| Context Window | 400K | 400K |
| Max Output Tokens | 128,000 | 128,000 |
| Open Source | No | No |
| Created | Dec 4, 2025 | Mar 17, 2026 |
The $10/M output pricing for GPT-5.1-Codex-Max versus $1.25/M for GPT-5.4 Nano suggests OpenAI is positioning Codex-Max as a specialized enterprise solution, likely with enhanced code generation consistency or additional fine-tuning on proprietary codebases. However, with both models sharing the same 400K context window and 128K max output, the 8x premium appears difficult to justify purely on technical merits unless your use case specifically benefits from Codex-Max's training distribution.
The $1.25/M input pricing for Codex-Max versus $0.20/M for Nano represents a significant premium that only makes sense if you're specifically leveraging code-optimized behaviors not captured in the 61/100 benchmark score. Since both models share identical capabilities (Vision, Function Calling, Streaming, JSON Mode, Reasoning, Web Search), the decision hinges on whether Codex-Max's specialized training provides tangible benefits for your specific programming languages or frameworks that justify a 6.25x-8x cost multiplier.
GPT-5.4 Nano's native file handling capability means you can directly process codebases, documentation PDFs, or binary assets without preprocessing, while Codex-Max requires converting everything to text or images first. This modality difference becomes critical for repository-scale analysis or automated code review pipelines, where Nano's $0.20/M input cost combined with direct file processing could process entire codebases 6.25x cheaper than Codex-Max's text-only approach.
At maximum output (128K tokens), a single GPT-5.1-Codex-Max response costs $1.28 versus $0.16 for GPT-5.4 Nano, making iterative code generation or multi-file scaffolding prohibitively expensive on Codex-Max. For context, generating a 100-file microservice architecture (averaging 1.28K tokens per file) would cost $128 with Codex-Max versus $16 with Nano, suggesting Codex-Max is optimized for high-value, single-shot generations rather than exploratory coding workflows.
The 8x output price differential between GPT-5.1-Codex-Max ($10/M) and GPT-5.4 Nano ($1.25/M) despite identical scores suggests OpenAI is segmenting by use case rather than raw performance - likely targeting Codex-Max at enterprise customers requiring specific compliance, latency, or support guarantees not reflected in public benchmarks. The 3-position rank difference (#12 vs #15 out of 326) indicates the market values Nano's cost efficiency over whatever specialized optimizations Codex-Max provides.