| Signal | GPT-5.1-Codex-Max | Delta | Nemotron Nano 9B V2 |
|---|---|---|---|
Capabilities | 100 | +33 | |
Pricing | 10 | +10 | |
Context window size | 89 | +8 | |
Recency | 100 | +2 | |
Output Capacity | 85 | +65 | |
| Overall Result | 5 wins | of 5 | 0 wins |
30
days ranked higher
0
days
0
days ranked higher
OpenAI
NVIDIA
Nemotron Nano 9B V2 saves you $613.00/month
That's $7356.00/year compared to GPT-5.1-Codex-Max at your current usage level of 100K calls/month.
| Metric | GPT-5.1-Codex-Max | Nemotron Nano 9B V2 | Winner |
|---|---|---|---|
| Overall Score | 96 | 69 | GPT-5.1-Codex-Max |
| Rank | #12 | #147 | GPT-5.1-Codex-Max |
| Quality Rank | #12 | #147 | GPT-5.1-Codex-Max |
| Adoption Rank | #12 | #147 | GPT-5.1-Codex-Max |
| Parameters | -- | 9B | -- |
| Context Window | 400K | 131K | GPT-5.1-Codex-Max |
| Pricing | $1.25/$10.00/M | $0.04/$0.16/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | GPT-5.1-Codex-Max |
| Pricing | 10 | 0 | GPT-5.1-Codex-Max |
| Context window size | 89 | 81 | GPT-5.1-Codex-Max |
| Recency | 100 | 98 | GPT-5.1-Codex-Max |
| Output Capacity | 85 | 20 | GPT-5.1-Codex-Max |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 96/100 (rank #12), placing it in the top 96% of all 290 models tracked.
Scores 69/100 (rank #147), placing it in the top 50% of all 290 models tracked.
GPT-5.1-Codex-Max has a 27-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Nemotron Nano 9B V2 offers 98% better value per quality point. At 1M tokens/day, you'd spend $3.00/month with Nemotron Nano 9B V2 vs $168.75/month with GPT-5.1-Codex-Max — a $165.75 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. Nemotron Nano 9B V2 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 ($0.16/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (96/100) 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 clearly outperforms Nemotron Nano 9B V2 with a significant 26.700000000000003-point lead. For most general use cases, GPT-5.1-Codex-Max is the stronger choice. However, Nemotron Nano 9B V2 may still excel in niche scenarios.
Best for Quality
GPT-5.1-Codex-Max
Marginally better benchmark scores; both are excellent
Best for Cost
Nemotron Nano 9B V2
98% 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 | Nemotron Nano 9B V2 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
NVIDIA
Nemotron Nano 9B V2 saves you $13.99/month
That's 98% 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 | Nemotron Nano 9B V2 |
|---|---|---|
| Context Window | 400K | 131K |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | Dec 4, 2025 | Sep 5, 2025 |
GPT-5.1-Codex-Max scores 96/100 (rank #12) compared to Nemotron Nano 9B V2's 69/100 (rank #147), giving it a 27-point advantage. GPT-5.1-Codex-Max is the stronger overall choice, though Nemotron Nano 9B V2 may excel in specific areas like cost efficiency.
GPT-5.1-Codex-Max is ranked #12 and Nemotron Nano 9B V2 is ranked #147 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Nemotron Nano 9B V2 is cheaper at $0.16/M output tokens vs GPT-5.1-Codex-Max's $10.00/M output tokens — 62.5x more expensive. Input token pricing: GPT-5.1-Codex-Max at $1.25/M vs Nemotron Nano 9B V2 at $0.04/M.
GPT-5.1-Codex-Max has a larger context window of 400,000 tokens compared to Nemotron Nano 9B V2's 131,072 tokens. A larger context window means the model can process longer documents and conversations.