Rank #1
xAI: Grok 4.20 Multi-Agent
- Agent
- 2.0M ctx
- 1M
- $1.88
Model · Vendors
Ranked models from this vendor or team on Global rankings (same data snapshot as the main global board).
Board snapshot:
xAI builds Grok frontier models for real-time, tool-use, and multimodal chat with aggressive context and pricing moves on aggregators. AI Hippo tracks Grok SKUs with Global Rankings placement and snapshot OpenRouter quotes—Compare Grok against GPT, Claude, and Gemini from the same board.
Rank #1
Rank #26
Rank #59
| Rank | Name | Type | Key metric | 1M tokens (avg) |
|---|---|---|---|---|
| 1 | xAI: Grok 4.20 Multi-Agent | Agent | 2.0M ctx | $1.88 |
| 26 | xAI: Grok Latest | Multimodal | 500k ctx | $4.00 |
| 59 | xAI: Grok 4.20 | Multimodal | 2.0M ctx | $1.88 |
| Rank | Name | Size | Price | Notes |
|---|---|---|---|---|
| — | xAI: Grok 4.20 | 2.0M ctx | $1.88/1M | x-ai/grok-4.20 |
| — | xAI: Grok 4.20 Multi-Agent | 2.0M ctx | $1.88/1M | x-ai/grok-4.20-multi-agent |
| — | xAI: Grok 4.3 | 1.0M ctx | $1.88/1M | x-ai/grok-4.3 |
| — | xAI: Grok 4.5 | 500k ctx | $4.00/1M | x-ai/grok-4.5 |
| — | xAI: Grok Build 0.1 | 256k ctx | $1.50/1M | x-ai/grok-build-0.1 |
| — | xAI: Grok Latest | 500k ctx | $4.00/1M | ~x-ai/grok-latest |
Counts and prices come from the OpenRouter catalog snapshot merged with AI Hippo Global rankings (same snapshot as /rankings/). Rank reflects the composite score on that board—not LMSYS Chatbot Arena ELO. Snapshot date: 2026-08-02. Methodology
xAI: Grok 4.20 Multi-Agent currently ranks #1 on AI Hippo's Global rankings board (snapshot 2026-08-02).
Across catalog and ranked rows, blended 1M-token prices range from $1.50 to $4.00 in the latest snapshot (2026-08-02). Check individual model pages for prompt vs completion splits.
3 of 6 catalog models appear on Global rankings; the remaining 3 are listed under catalog-only on this page.
Yes—use the compare link on this page or open /en/compare/?m=xAI%3A%20Grok%204.20%20Multi-Agent&m=xAI%3A%20Grok%20Latest to side-by-side context, price, and composite score for the top ranked models.
Global rankings uses on-site weighting (context window first, then blended 1M-token price)—not third-party ELO. Full methodology: /en/methodology/