Head-to-Head Model Comparison

ERNIE Lite vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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BaiduGooglelightweightflagship

Compare ERNIE Lite by Baidu against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.

Comparación Directa (VS)

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Popular Matchups:
Baidu

ERNIE Lite

El ERNIE más económico

Baidu smallest modelo de lenguaje desarrollado para minimal memoria consumption, alto transmisión rendimiento, y alto-volumen background jobs.

Intelligence Index65 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Google

Gemini 4 Argon

Rey multimodal con salida de 1M

Google de DeepMind insignia de frontera razonamiento motor con 1-millones-token salida limits, autónomo cybersecurity defense, y en tiempo real audio/visión ingesta.

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Diferencias Clave de un Vistazo

  • ERNIE Lite is 1.0x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon has a larger context window (1M vs 128K tokens).
  • ERNIE Lite is faster at 190 tok/s vs 115 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaERNIE LiteGemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
6597
Provider
BaiduGoogle
Input Price
Cost per million input tokens
$0.00 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K1000K
Throughput Speed
Tokens generated per second
190 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
N/A81.9%
GPQA Diamond
Graduate-level reasoning
N/A81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.10 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código

Evaluations ongoing

Costo
ERNIE Lite
1.0x cheaper monthly runtime
Velocidad
ERNIE Lite
+65% faster generation
Contexto
Gemini 4 Argon
1M tokens window

Puntuaciones de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

ERNIE LiteGemini 4 Argon
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

N/Avs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

N/Avs81.5%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

61%vs90.8%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1180ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs57.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs80.5%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs94.8%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

190 tok/s vs115 tok/s

Latencia y Tiempo de Respuesta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
ERNIE Lite0.20s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
ERNIE Lite2.83s
Gemini 4 Argon5.20s

Simulador Interactivo de Costos de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
ERNIE Lite Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
ERNIE Lite saves approximately $12.15 / month (100%) under this workload.1.0x Savings

ERNIE Lite · Strengths & Key Advantages

  • Completely free nivel access en Baidu Qianfan platform
  • Blazing rápido generación exceeding 190 tokens por second
  • Minimal resource huella suitable para embedded perimetral devices
Considerations & Trade-offs
  • bajo precisión en subtle linguistic nuances o complejo multipaso razonamiento
  • alto rate de hallucination cuando pushed beyond straightforward facts

Gemini 4 Argon · Strengths & Key Advantages

  • Groundbreaking 1,000,000 token maximum salida generación capacidad via largo Decode Continuation
  • 1M-token entrada window con 99.7% GraphWalks recall (84.2% en el 256K-1M range)
  • nativo procesamiento de completo audio, video streams, y visual datos (91.7% en LVBench)
  • Half el token precio de de Anthropic Opus 5.5 y #1 en Chatbot Arena (1525 Elo)
Considerations & Trade-offs
  • masivo token outputs puede incur alto absolute costos if unconstrained (~62K salida tokens por index tarea)
  • $2/$10 precios es un introductory 50% discount; estándar rates revert un $4/$20 once el promotion ends

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricERNIE LiteGemini 4 Argon
Cost per Task
Estimated USD to finish one task
$0.00$2.45
Output Tokens / Task
Tokens generated per task
6K75K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaERNIE LiteGemini 4 Argon
Official API Model ID (SDK)ernie-litemodels/gemini-4-argon
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2024-032026-09
Knowledge CutoffDecember 2023June 2026
ArchitectureUltra-Lightweight Edge-Ready TransformerPathways Multimodal Sparse Mixture-of-Experts
ParametersConfidential / 3B ScaleConfidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Free across full context window (only KV-cache VRAM scales)Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)Implicit + Explicit Context Caching at $0.1/1M with configurable TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 6 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Google DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision, audio, video
Output Modalitiestexttext

ERNIE Lite vs Gemini 4 Argon: Respuestas Rápidas (FAQ)

Which is more intelligent, ERNIE Lite or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 65 on the composite Intelligence Index.

Which model is faster?

ERNIE Lite is faster, generating 190 tokens per second compared with 115 tokens per second.

Which model is cheaper to run?

ERNIE Lite is cheaper at $0.00 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

ERNIE Lite has lower latency, with a time to first token of 0.20s compared with 0.85s.

Which model has a larger context window?

Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 128K tokens.

Veredicto

Choose ERNIE Lite for alto-frequency keyword etiquetado, basic intent enrutamiento, y embedded device nlp, or choose Gemini 4 Argon for whole-repositorio generación de código, completo-book síntesis, video comprensión, y multi-hour audio procesamiento.

Preguntas frecuentes

Which is cheaper: ERNIE Lite or Gemini 4 Argon?+

ERNIE Lite costs $0/1M input and $0/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: ERNIE Lite or Gemini 4 Argon?+

ERNIE Lite supports 128K tokens whereas Gemini 4 Argon supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.

Fuentes: Baidu & Google Official Documentation