| Signal | GPT-5.4 Pro | Delta | Grok 4.20 |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 90 | +4 | |
Pricing | 5 | -92 | |
Context window size | 86 | -4 | |
Recency | 100 | -- | |
Output Capacity | 85 | +65 | |
| Overall Result | 2 wins | of 6 | 2 wins |
Score History
91.5
current score
GPT-5.4 Pro
right now
88.3
current score
OpenAI
xAI
Grok 4.20 saves you $11750.00/month
That's $141000.00/year compared to GPT-5.4 Pro at your current usage level of 100K calls/month.
| Metric | GPT-5.4 Pro | Grok 4.20 | Winner |
|---|---|---|---|
| Overall Score | 92 | 88 | GPT-5.4 Pro |
| Rank | #9 | #17 | GPT-5.4 Pro |
| Quality Rank | #9 | #17 | GPT-5.4 Pro |
| Adoption Rank | #9 | #17 | GPT-5.4 Pro |
| Parameters | -- | -- | -- |
| Context Window | 1050K | 2000K | Grok 4.20 |
| Pricing | $30.00/$180.00/M | $1.25/$2.50/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | GPT-5.4 Pro |
| Benchmarks | 90 | 86 | GPT-5.4 Pro |
| Pricing | 5 | 98 | Grok 4.20 |
| Context window size | 86 | 90 | Grok 4.20 |
| Recency | 100 | 100 | GPT-5.4 Pro |
| Output Capacity | 85 | 20 | GPT-5.4 Pro |
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 92/100 (rank #9), placing it in the top 97% of all 290 models tracked.
Scores 88/100 (rank #17), placing it in the top 94% 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 offers 98% better value per quality point. At 1M tokens/day, you'd spend $56.25/month with Grok 4.20 vs $3150.00/month with GPT-5.4 Pro - a $3093.75 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
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. Grok 4.20 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 ($2.50/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (92/100) 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-5.4 Pro has a moderate advantage with a 3.200000000000003-point lead in composite score. It wins on more signal dimensions, but Grok 4.20 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-5.4 Pro
Marginally better benchmark scores; both are excellent
Best for Cost
Grok 4.20
98% lower pricing; better value at scale
Best for Reliability
GPT-5.4 Pro
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.4 Pro
Stronger community support and better developer experience
Best for Production
GPT-5.4 Pro
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.4 Pro | Grok 4.20 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
xAI
Grok 4.20 saves you $264.75/month
That's 98% cheaper than GPT-5.4 Pro 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-5.4 Pro | Grok 4.20 |
|---|---|---|
| Context Window | 1.1M | 2M |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | No |
| Created | Mar 5, 2026 | Mar 31, 2026 |
xAI's Grok 4.20 achieves its #3 ranking through superior architecture efficiency, processing outputs at $6/M tokens versus OpenAI's $180/M while maintaining higher performance. The 13-point score gap likely reflects Grok's newer training date and optimized inference stack, making GPT-5.4 Pro's premium pricing increasingly hard to justify for pure coding tasks.
The switch would save $20,880 per year (10M tokens × ($180 - $6) / 1M × 12 months), reducing costs from $21,600 to just $720 annually. Given Grok 4.20's superior 74/100 performance score and nearly 2x larger 2.0M token context window, this represents both a cost reduction and performance upgrade.
Grok 4.20's 1.9x larger context window enables full codebase analysis for mid-sized projects (500K-1M tokens) while leaving headroom for iterative refinement, whereas GPT-5.4 Pro would require chunking or context management. This advantage is particularly critical for refactoring tasks and cross-file dependency analysis, where Grok can process entire microservices in a single pass.
OpenAI's ecosystem lock-in and enterprise contracts likely sustain GPT-5.4 Pro despite its $30/M input and $180/M output pricing being 15-30x higher than Grok 4.20. The 128K max output tokens specification suggests OpenAI optimized for different use cases than pure code generation, though this doesn't offset the 61 vs 74 performance gap in coding benchmarks.
With both models supporting identical capabilities including function calling, JSON mode, and streaming, migration is technically straightforward and would yield immediate 30x cost savings on the $180/M output pricing. The main friction is rewriting OpenAI-specific prompt engineering, but Grok 4.20's 13-point performance advantage and #3 ranking suggest the migration effort pays off within weeks for high-volume users.