Head-to-Head Model Comparison

ERNIE Speed vs ERNIE Lite

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
ERNIE Speed vs ERNIE Lite: Benchmarks, Pricing & Speed Comparison

ERNIE Speed di Baidu e ERNIE Lite di Baidu sono due modelli di IA di riferimento. ERNIE Speed offre una finestra di contesto di 128K token a $0.00/$0.00 per milione di token, mentre ERNIE Lite mette a disposizione 128K token di contesto a $0.00/$0.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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Popular Matchups:
Baidu

ERNIE Speed

Inferenza Ultra-Rapida

ERNIE Speed di Baidu è un modello di IA progettato per le interazioni in tempo reale a bassissima latenza e il routing ad alto volume, con finestra di contesto da 128K, velocità di 175 token/s, indice di intelligenza di 68/100 e tariffa di

Intelligence Index68 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Baidu

ERNIE Lite

Modello Leggero ed Economico

ERNIE Lite di Baidu è un modello di IA progettato per la massima efficienza dei costi per token e l’inferenza rapida in produzione, con finestra di contesto da 128K, velocità di 190 token/s, indice di intelligenza di 65/100 e tariffa di acc

Intelligence Index65 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

  • Both models cost the same under this workload — choose on capability, not price.
  • ERNIE Lite is faster at 190 tok/s vs 175 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureERNIE SpeedERNIE Lite
Intelligence Index
Composite reasoning & knowledge score (0-100)
6865
Provider
BaiduBaidu
Input Price
Cost per million input tokens
$0.00 / 1M$0.00 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$0.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$0.00 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
175 tok/s190 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A

Chi vince in ogni categoria?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Tied
Identical monthly runtime cost
Speed
ERNIE Lite
+9% faster generation
Context
Tied
128K tokens window

Punteggi Benchmark Verificati

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

ERNIE SpeedERNIE Lite
MMLU-Pro (Multi-task Language Understanding)

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

64%vs61%
LMSYS Chatbot Arena Elo

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

1205ptsvs1180pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

175 tok/s vs190 tok/s

Latenza e Tempo di Risposta

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 Speed0.23s
ERNIE Lite0.20s
Est. End-to-End Response (500 tokens)TTFT + generation time
ERNIE Speed3.09s
ERNIE Lite2.83s

Simulatore Interattivo dei Costi Token

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 Speed Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
ERNIE Lite Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
These models cost the same under this workload — no savings either way.Break-even

ERNIE Speed · Strengths & Key Advantages

  • Finestra di contesto da 128K con capacità massima di output fino a 4K token (MMLU-Pro 64% · Arena Elo 1205)
  • Throughput elevato di 175 token/secondo con latenza al primo token (TTFT) di soli 230 ms
  • Pesi aperti (Confidential / 8B Scale) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
  • Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

ERNIE Lite · Strengths & Key Advantages

  • Finestra di contesto da 128K con capacità massima di output fino a 4K token (MMLU-Pro 61% · Arena Elo 1180)
  • Throughput elevato di 190 token/secondo con latenza al primo token (TTFT) di soli 200 ms
  • Pesi aperti (Confidential / 3B Scale) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
  • Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

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

MetricERNIE SpeedERNIE Lite
Cost per Task
Estimated USD to finish one task
$0.00$0.00
Output Tokens / Task
Tokens generated per task
8K6K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureERNIE SpeedERNIE Lite
Official API Model ID (SDK)ernie-speedernie-lite
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2024-032024-03
Knowledge CutoffDecember 2023December 2023
ArchitectureDistilled High-Throughput TransformerUltra-Lightweight Edge-Ready Transformer
ParametersConfidential / 8B ScaleConfidential / 3B Scale
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Free across full context window (only KV-cache VRAM scales)Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)Automatic prefix KV-caching in vLLM / SGLang (0 cost)
Computer Use / GUI AgentAPI / 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 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 toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 6 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext
Output Modalitiestexttext

ERNIE Speed vs ERNIE Lite: Risposte Rapide (FAQ)

Which is more intelligent, ERNIE Speed or ERNIE Lite?

ERNIE Speed is more intelligent. It scores 68 compared with 65 on the composite Intelligence Index.

Which model is faster?

ERNIE Lite is faster, generating 190 tokens per second compared with 175 tokens per second.

Which model has lower latency?

ERNIE Lite has lower latency, with a time to first token of 0.20s compared with 0.23s.

Verdetto

Sia ERNIE Speed (Ideale per le interazioni in tempo reale a bassissima latenza e il routing ad alto volume, sistemi RAG aziendali e integrazioni API scalabili.) sia ERNIE Lite (Ideale per la massima efficienza dei costi per token e l’inferenza rapida in produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: ERNIE Speed guida nei benchmark di ragionamento e programmazione, ERNIE Lite garantisce una generazione più rapida e ERNIE Speed offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, ERNIE Speed o ERNIE Lite?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale ERNIE Speed. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra ERNIE Speed e ERNIE Lite?+

ERNIE Speed costa $0.00 / $0.00 per milione di token di input/output, mentre ERNIE Lite costa $0.00 / $0.00. Nel costo combinato, ERNIE Speed risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

ERNIE Speed supporta 128K token di contesto contro 128K token di ERNIE Lite, mentre ERNIE Lite offre una velocità di generazione superiore.

AI Terminology & Guide
Explore Glossary →

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

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.

Fonti ufficiali: Documentazione API ufficiale di Baidu e Baidu, schede di sistema e benchmark indipendenti (2026).