ERNIE Lite vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare ERNIE Lite by Baidu against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
Cambia y Compara Cualquier Modelo
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Live comparison: no in-depth editorial review has been published for this pair yet.
ERNIE Lite
El ERNIE más económicoBaidu smallest modelo de lenguaje desarrollado para minimal memoria consumption, alto transmisión rendimiento, y alto-volumen background jobs.
$0.00 / 1M
$0.00 / 1M
128K tokens
N/A
GPT-6.1 Sol
Valor cercano a Astraofrece results close un GPT-6 Astra un roughly one fifth del precio — el latest 2026 lanzamiento.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Diferencias Clave de un Vistazo
- ERNIE Lite is 1.0x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol has a larger context window (1M vs 128K tokens).
- ERNIE Lite is faster at 190 tok/s vs 120 tok/s.
| Característica | ERNIE Lite | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 65 | 94 |
Provider | Baidu | OpenAI |
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 text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 4K | 128K |
Throughput Speed Tokens generated per second | 190 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.3% |
GPQA Diamond Graduate-level reasoning | N/A | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.10 / 1M |
¿Quién gana en cada área?
At-a-glance decision frameworkEvaluations ongoing
Puntuaciones de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
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.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
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
GPT-6.1 Sol · Strengths & Key Advantages
- Near-Astra results un roughly un fifth del costo
- Excellent codificación y de largo alcance agente rendimiento
- sólido reliability con far menor latencia que Astra
- Near-insignia results un roughly un fifth del precio
Considerations & Trade-offs
- Still marginally behind Astra en el muy hardest razonamiento
- Same precio as GPT-6 Sol, so el upgrade decision es easy
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | ERNIE Lite | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.00 | $2.05 |
Output Tokens / Task Tokens generated per task | 6K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | ERNIE Lite | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | ernie-lite | gpt-6-1-sol |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-03 | 2026-09 |
| Knowledge Cutoff | December 2023 | April 2026 |
| Architecture | Ultra-Lightweight Edge-Ready Transformer | Near-Astra unified reasoning model |
| Parameters | Confidential / 3B Scale | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 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) | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | Automatic prefix caching at $0.1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | BF16 / 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 Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
ERNIE Lite vs GPT-6.1 Sol: Respuestas Rápidas (FAQ)
Which is more intelligent, ERNIE Lite or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 65 on the composite Intelligence Index.
Which model is faster?
ERNIE Lite is faster, generating 190 tokens per second compared with 120 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 1.12s.
Which model has a larger context window?
GPT-6.1 Sol 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 GPT-6.1 Sol for el mejor valor modelo de frontera para profesional y agentic trabajo.
Preguntas frecuentes
Which is cheaper: ERNIE Lite or GPT-6.1 Sol?+
ERNIE Lite costs $0/1M input and $0/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: ERNIE Lite or GPT-6.1 Sol?+
ERNIE Lite supports 128K tokens whereas GPT-6.1 Sol supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Aion-3.0 vs Aion-Mini: Benchmarks, Pricing & Speed ComparisonComparar
- Aion-3.0 vs Gemini 3.6 Flash: Benchmarks, Pricing & Speed ComparisonComparar
- Aion-Mini vs Laguna XS 2.1: Benchmarks, Pricing & Speed ComparisonComparar
- Aya Expanse 32B vs Llama 3.2 90B Vision: Benchmarks, Pricing & Speed ComparisonComparar
- Aya Expanse 8B vs Command R+: Benchmarks, Pricing & Speed ComparisonComparar
- Aya Expanse 8B vs Qwen 2.5 7B Instruct: Benchmarks, Pricing & Speed ComparisonComparar
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 & OpenAI Official Documentation