ERNIE 5.0 vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare ERNIE 5.0 by Baidu against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.
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ERNIE 5.0
Model Unggulan Garis DepanERNIE 5.0 dari Baidu adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 128K, kecepatan 70 token/detik, indeks kecerdasan 90/100, serta tarif $1.5
$1.50 / 1M
$6.00 / 1M
128K tokens
60%
Gemini 4 Argon
AI Multimodal AsliGemini 4 Argon dari Google adalah model AI yang dirancang untuk pemahaman multimodal asli (teks & visual) serta analisis dokumen kompleks, menghadirkan jendela konteks 1M, kecepatan 115 token/detik, indeks kecerdasan 97/100, serta tarif $2/
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Perbedaan Utama Sekilas
- ERNIE 5.0 is 1.5x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon has a larger context window (1M vs 128K tokens).
- Gemini 4 Argon is faster at 115 tok/s vs 70 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 60.0%).
| Feature | ERNIE 5.0 | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 90 | 97 |
Provider | Baidu | |
Input Price Cost per million input tokens | $1.50 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $6.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.01 / 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 | 16K | 1000K |
Throughput Speed Tokens generated per second | 70 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 60% | 81.9% |
GPQA Diamond Graduate-level reasoning | 74.5% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.15 / 1M | $0.10 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
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.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
ERNIE 5.0 · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 60% · GPQA Diamond 74.5%)
- Kecepatan generasi tinggi 70 token/detik dengan latensi token pertama (TTFT) hanya 580 ms
- Skema harga API kompetitif (tarif $1.5/$6 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
- Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Gemini 4 Argon · Strengths & Key Advantages
- Jendela konteks 1M dengan kapasitas output maksimum hingga 1M token (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
- Kecepatan generasi tinggi 115 token/detik dengan latensi token pertama (TTFT) hanya 850 ms
- Skema harga API kompetitif (tarif $2/$10 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
- Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
- Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | ERNIE 5.0 | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.32 | $2.45 |
Output Tokens / Task Tokens generated per task | 25K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 9K | 36K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | ERNIE 5.0 | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | ernie-5-0 | models/gemini-4-argon |
| API Protocol | Baidu REST API (OpenAI-Compatible) | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2026-05 | 2026-09 |
| Knowledge Cutoff | February 2026 | June 2026 |
| Architecture | Colossus-Scale Omnimodal MoE Transformer | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | 800B total (45B active MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($1.5/1M in) across full 128K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.15/1M tokens | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | 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 | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Vertex AI Supervised Adapter Tuning & Context Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) | 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 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 | Google DeepMind Frontier Safety Framework 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, video | text, vision, audio, video |
| Output Modalities | text | text |
ERNIE 5.0 vs Gemini 4 Argon: Jawaban Cepat (FAQ)
Which is more intelligent, ERNIE 5.0 or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 90 on the composite Intelligence Index.
Which model is faster?
Gemini 4 Argon is faster, generating 115 tokens per second compared with 70 tokens per second.
Which model is cheaper to run?
ERNIE 5.0 is cheaper at $1.01 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
ERNIE 5.0 has lower latency, with a time to first token of 0.58s 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.
Kesimpulan
Choose ERNIE 5.0 for sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi ai, sistem rag perusahaan, dan integrasi api skala produksi., or choose Gemini 4 Argon for sangat cocok untuk pemahaman multimodal asli (teks & visual) serta analisis dokumen kompleks, sistem rag perusahaan, dan integrasi api skala produksi..
Pertanyaan Umum (FAQ)
Which is cheaper: ERNIE 5.0 or Gemini 4 Argon?+
ERNIE 5.0 costs $1.5/1M input and $6/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: ERNIE 5.0 or Gemini 4 Argon?+
ERNIE 5.0 supports 128K tokens whereas Gemini 4 Argon supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Sumber resmi: Baidu & Google Official Documentation