| Signal | Rnj 1 Instruct | Delta | GPT-5.1-Codex-Max |
|---|---|---|---|
Capabilities | 50 | -50 | |
Pricing | 0 | -10 | |
Context window size | 72 | -17 | |
Recency | 100 | -- | |
Output Capacity | 20 | -65 | |
| Overall Result | 0 wins | of 5 | 4 wins |
12
days higher
1
days
17
days higher
essentialai
OpenAI
Rnj 1 Instruct saves you $602.50/month
That's $7230.00/year compared to GPT-5.1-Codex-Max at your current usage level of 100K calls/month.
| Metric | Rnj 1 Instruct | GPT-5.1-Codex-Max | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #164 | #165 | Rnj 1 Instruct |
| Quality Rank | #164 | #165 | Rnj 1 Instruct |
| Adoption Rank | #164 | #165 | Rnj 1 Instruct |
| Parameters | -- | -- | -- |
| Context Window | 33K | 400K | GPT-5.1-Codex-Max |
| Pricing | $0.15/$0.15/M | $1.25/$10.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 100 | GPT-5.1-Codex-Max |
| Pricing | 0 | 10 | GPT-5.1-Codex-Max |
| Context window size | 72 | 89 | GPT-5.1-Codex-Max |
| Recency | 100 | 100 | Rnj 1 Instruct |
| Output Capacity | 20 | 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%). Here's what the scores mean for these two models:
Scores 40/100 (rank #164), placing it in the top 44% of all 290 models tracked.
Scores 40/100 (rank #165), placing it in the top 43% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Rnj 1 Instruct offers 97% better value per quality point. At 1M tokens/day, you'd spend $4.50/month with Rnj 1 Instruct vs $168.75/month with GPT-5.1-Codex-Max - a $164.25 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Rnj 1 Instruct 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 ($0.15/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) 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
Rnj 1 Instruct and GPT-5.1-Codex-Max are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Rnj 1 Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Rnj 1 Instruct
97% lower pricing; better value at scale
Best for Reliability
Rnj 1 Instruct
Higher uptime and faster response speeds
Best for Prototyping
Rnj 1 Instruct
Stronger community support and better developer experience
Best for Production
Rnj 1 Instruct
Wider enterprise adoption and proven at scale
by essentialai
| Capability | Rnj 1 Instruct | GPT-5.1-Codex-Max |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
essentialai
OpenAI
Rnj 1 Instruct saves you $13.80/month
That's 97% 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 | Rnj 1 Instruct | GPT-5.1-Codex-Max |
|---|---|---|
| Context Window | 33K | 400K |
| Max Output Tokens | -- | 128,000 |
| Open Source | Yes | No |
| Created | Dec 7, 2025 | Dec 4, 2025 |
Both Rnj 1 Instruct and GPT-5.1-Codex-Max score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Rnj 1 Instruct is ranked #164 and GPT-5.1-Codex-Max is ranked #165 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Rnj 1 Instruct is cheaper at $0.15/M output tokens vs GPT-5.1-Codex-Max's $10.00/M output tokens - 66.7x more expensive. Input token pricing: Rnj 1 Instruct at $0.15/M vs GPT-5.1-Codex-Max at $1.25/M.
GPT-5.1-Codex-Max has a larger context window of 400,000 tokens compared to Rnj 1 Instruct's 32,768 tokens. A larger context window means the model can process longer documents and conversations.