ERNIE 4.5 vs ERNIE X1
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
ERNIE 4.5 by Baidu and ERNIE X1 by Baidu represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, ERNIE X1 holds a notable pricing advantage for token ingestion. On output generation, ERNIE X1 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 128K tokens. In latency-sensitive production environments, ERNIE 4.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
원하는 AI 모델 선택 및 실시간 비교
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
ERNIE 4.5
심층 추론 모델Baidu의 ERNIE 4.5 모델은 128K 토큰 컨텍스트 윈도우와 입력 $0.6/1M 토큰, 출력 $2.4/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$0.60 / 1M
$2.40 / 1M
128K tokens
N/A
ERNIE X1
심층 추론 모델Baidu의 ERNIE X1 모델은 128K 토큰 컨텍스트 윈도우와 입력 $0.4/1M 토큰, 출력 $1.6/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$0.40 / 1M
$1.60 / 1M
128K tokens
N/A
한눈에 보는 핵심 차이점
- ERNIE X1 is 1.5x cheaper for API usage (input + output tokens combined).
- ERNIE 4.5 is faster at 75 tok/s vs 65 tok/s.
| Feature | ERNIE 4.5 | ERNIE X1 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 81 | 82 |
Provider | Baidu | Baidu |
Input Price Cost per million input tokens | $0.60 / 1M | $0.40 / 1M |
Output Price Cost per million output tokens | $2.40 / 1M | $1.60 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.40 / 1M | $0.27 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 8K | 16K |
Throughput Speed Tokens generated per second | 75 tok/s | 65 tok/s |
SWE-bench Verified Real-world software engineering | N/A | N/A |
GPQA Diamond Graduate-level reasoning | 60% | 65% |
Cached Input Price Prompt caching discount per 1M tokens | $0.06 / 1M | $0.04 / 1M |
부문별 우위 모델
At-a-glance decision frameworkEvaluations ongoing
검증된 벤치마크 점수 비교
Official evaluation metrics verified by independent third-party research labs.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Tokens emitted per second during active generation streaming.
지연 시간(Latency) 및 응답 속도
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
실시간 API 토큰 비용 시뮬레이터
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
ERNIE 4.5 · Strengths & Key Advantages
- Baidu의 첨단 Multimodal Foundation Knowledge Transformer 아키텍처와 최대 128K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $0.6/1M, 출력 $2.4/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
ERNIE X1 · Strengths & Key Advantages
- Baidu의 첨단 Deep Deliberate Reasoning Transformer 아키텍처와 최대 128K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $0.4/1M, 출력 $1.6/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | ERNIE 4.5 | ERNIE X1 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.16 | $0.14 |
Output Tokens / Task Tokens generated per task | 18K | 20K |
Reasoning Tokens / Task Thinking tokens burned per task | 4K | 11K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | ERNIE 4.5 | ERNIE X1 |
|---|---|---|
| Official API Model ID (SDK) | ernie-4-5 | ernie-x1 |
| API Protocol | Baidu REST API (OpenAI-Compatible) | Baidu REST API (OpenAI-Compatible) |
| Release Date | 2025-03 | 2025-03 |
| Knowledge Cutoff | December 2024 | January 2025 |
| Architecture | Multimodal Foundation Knowledge Transformer | Deep Deliberate Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.6/1M in) across full 128K window | Flat rate ($0.4/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Cached input at $0.06/1M tokens | Cached input at $0.04/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Baidu Production Safety & Alignment Verified | Baidu Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision, audio | text |
| Output Modalities | text | text |
ERNIE 4.5 vs ERNIE X1: 핵심 요약 문답 (FAQ)
Which is more intelligent, ERNIE 4.5 or ERNIE X1?
ERNIE X1 is more intelligent. It scores 82 compared with 81 on the composite Intelligence Index.
Which model is faster?
ERNIE 4.5 is faster, generating 75 tokens per second compared with 65 tokens per second.
Which model is cheaper to run?
ERNIE X1 is cheaper at $0.27 per 1M tokens blended, compared with $0.40 (7:2:1 cache:input:output ratio).
Which model has lower latency?
ERNIE 4.5 has lower latency, with a time to first token of 0.51s compared with 0.82s.
종합 평가
Verdict & Model Selection Recommendation: Choose ERNIE 4.5 if your priority is Chinese enterprise applications, local compliance and legal review, and multimodal knowledge search. Its performance in demanding tasks justifies its operational token cost. Choose ERNIE X1 if your workflow prioritizes Mathematical tutoring, competitive programming in Chinese, and structured business planning. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
자주 묻는 질문 (FAQ)
How does ERNIE 4.5 compare to ERNIE X1 in API token pricing and cost per token?+
ERNIE 4.5 costs $0.60 per 1M input tokens and $2.40 per 1M output tokens, whereas ERNIE X1 costs $0.40 input and $1.60 output. Overall, ERNIE X1 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: ERNIE 4.5 or ERNIE X1?+
Both ERNIE 4.5 and ERNIE X1 offer an identical context window of 128K tokens (~96k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: ERNIE 4.5 or ERNIE X1?+
ERNIE 4.5 scores at the frontier of coding benchmarks, while ERNIE X1 scores competitively for software generation. For complex autonomous debugging and agentic engineering, ERNIE 4.5 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between ERNIE 4.5 and ERNIE X1?+
ERNIE 4.5 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, ERNIE X1 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between ERNIE 4.5 and ERNIE X1?+
ERNIE 4.5 generates approximately 75 tokens per second, while ERNIE X1 delivers 65 tokens per second. In latency-sensitive production environments, ERNIE 4.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining ERNIE 4.5 and ERNIE X1 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to ERNIE X1 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to ERNIE 4.5. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- ERNIE 4.5 vs QwQ Plus: Benchmarks, Pricing & Speed Comparison비교
- ERNIE 5.0 vs ERNIE 4.5: Benchmarks, Pricing & Speed Comparison비교
- ERNIE X1 vs Amazon Nova Premier: Benchmarks, Pricing & Speed Comparison비교
- Magistral Medium vs ERNIE 4.5: Benchmarks, Pricing & Speed Comparison비교
- Aion-3.0 vs Aion-Mini: Benchmarks, Pricing & Speed Comparison비교
- Aion-3.0 vs Gemini 3.6 Flash: Benchmarks, Pricing & Speed Comparison비교
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
공식 출처: GetInfoUs Independent AI Benchmarks & Official API Specs