| Signal | GPT-5.3-Codex | Delta | Grok 4.20 Multi-Agent Beta |
|---|---|---|---|
Capabilities | 100 | +17 | |
Pricing | 14 | +8 | |
Context window size | 89 | -11 | |
Recency | 100 | -- | |
Output Capacity | 85 | +65 | |
| Overall Result | 3 wins | of 5 | 1 wins |
18
days ranked higher
5
days
7
days ranked higher
OpenAI
xAI
Grok 4.20 Multi-Agent Beta saves you $375.00/month
That's $4500.00/year compared to GPT-5.3-Codex at your current usage level of 100K calls/month.
| Metric | GPT-5.3-Codex | Grok 4.20 Multi-Agent Beta | Winner |
|---|---|---|---|
| Overall Score | 85 | 82 | GPT-5.3-Codex |
| Rank | #29 | #61 | GPT-5.3-Codex |
| Quality Rank | #29 | #61 | GPT-5.3-Codex |
| Adoption Rank | #29 | #61 | GPT-5.3-Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 2000K | Grok 4.20 Multi-Agent Beta |
| Pricing | $1.75/$14.00/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 83 | GPT-5.3-Codex |
| Pricing | 14 | 6 | GPT-5.3-Codex |
| Context window size | 89 | 100 | Grok 4.20 Multi-Agent Beta |
| Recency | 100 | 100 | GPT-5.3-Codex |
| Output Capacity | 85 | 20 | GPT-5.3-Codex |
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 85/100 (rank #29), placing it in the top 90% of all 290 models tracked.
Scores 82/100 (rank #61), placing it in the top 79% of all 290 models tracked.
With only a 3-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.
Grok 4.20 Multi-Agent Beta offers 49% better value per quality point. At 1M tokens/day, you'd spend $120.00/month with Grok 4.20 Multi-Agent Beta vs $236.25/month with GPT-5.3-Codex - a $116.25 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. Grok 4.20 Multi-Agent Beta also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (2000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($6.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (85/100) 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-5.3-Codex and Grok 4.20 Multi-Agent Beta are extremely close in overall performance (only 2.799999999999997 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-5.3-Codex
Marginally better benchmark scores; both are excellent
Best for Cost
Grok 4.20 Multi-Agent Beta
49% lower pricing; better value at scale
Best for Reliability
GPT-5.3-Codex
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.3-Codex
Stronger community support and better developer experience
Best for Production
GPT-5.3-Codex
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.3-Codex | Grok 4.20 Multi-Agent Beta |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
xAI
Grok 4.20 Multi-Agent Beta saves you $9.15/month
That's 46% cheaper than GPT-5.3-Codex 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-5.3-Codex | Grok 4.20 Multi-Agent Beta |
|---|---|---|
| Context Window | 400K | 2M |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | No |
| Created | Feb 24, 2026 | Mar 12, 2026 |
GPT-5.3-Codex scores 85/100 (rank #29) compared to Grok 4.20 Multi-Agent Beta's 82/100 (rank #61), giving it a 3-point advantage. GPT-5.3-Codex is the stronger overall choice, though Grok 4.20 Multi-Agent Beta may excel in specific areas like cost efficiency.
GPT-5.3-Codex is ranked #29 and Grok 4.20 Multi-Agent Beta is ranked #61 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.
Grok 4.20 Multi-Agent Beta is cheaper at $6.00/M output tokens vs GPT-5.3-Codex's $14.00/M output tokens - 2.3x more expensive. Input token pricing: GPT-5.3-Codex at $1.75/M vs Grok 4.20 Multi-Agent Beta at $2.00/M.
Grok 4.20 Multi-Agent Beta has a larger context window of 2,000,000 tokens compared to GPT-5.3-Codex's 400,000 tokens. A larger context window means the model can process longer documents and conversations.