ERNIE X1.1 vs Grok 4.3
At a Glance
| Compare | ERNIE X1.1Baidu | Grok 4.3xAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #40 of 4616.6 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 11.1–44.4 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #7 of 44$0.028 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #33 of 3846.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 43.3–59.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $1.25Xai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $2.50Xai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 66K | 1,000K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 3, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | ERNIE X1.1 | Grok 4.3 |
|---|---|---|
| Developer | Baidu | xAI |
| Family | Ernie X1 | Grok 4 |
| Model | ERNIE X1.1 | Grok 4.3 |
| Version | ERNIE X1.1 | Grok 4.3 |
| Lifecycle | active | active |
| Released | 2025-09-26 | 2026-06-17 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 66K | 1,000K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Baidu Qianfan (Standard) | Xai (Standard) |
| Capabilities | agents, chat, reasoning, search, tools | chat, generation, reasoning, structured_outputs, tools |
ERNIE X1.1 Capabilities
Grok 4.3 Capabilities
Primary Evidence
Sources and Freshness
Questions
ERNIE X1.1 vs Grok 4.3 FAQs
Is ERNIE X1.1 or Grok 4.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE X1.1 and Grok 4.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, ERNIE X1.1 or Grok 4.3?+
ERNIE X1.1 is $1.00 and Grok 4.3 is $1.25 per million tokens, so ERNIE X1.1 is cheaper on this metric. ERNIE X1.1 is $4.00 and Grok 4.3 is $2.50 per million tokens, so Grok 4.3 is cheaper on this metric.
Which has a larger context window, ERNIE X1.1 or Grok 4.3?+
Grok 4.3 has the larger sourced context window. ERNIE X1.1 supports 66K and Grok 4.3 supports 1,000K.
Which performs better in benchmarks, ERNIE X1.1 or Grok 4.3?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can ERNIE X1.1 or Grok 4.3 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. ERNIE X1.1 is not marked open weight; Grok 4.3 is not marked open weight.
Can ERNIE X1.1 and Grok 4.3 understand images?+
ERNIE X1.1 is not documented with image input; Grok 4.3 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, ERNIE X1.1 or Grok 4.3?+
Neither has a larger sourced maximum output. ERNIE X1.1 is 66K and Grok 4.3 is —.
Do ERNIE X1.1 and Grok 4.3 support reasoning and tool use?+
ERNIE X1.1: reasoning and tool calling. Grok 4.3: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, ERNIE X1.1 or Grok 4.3?+
ERNIE X1.1 has 1 sourced provider route; Grok 4.3 has 1, a tie.
Which offers better value, ERNIE X1.1 or Grok 4.3?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.