Gemini 3.5 Live Translate vs GPT Realtime Whisper
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Gemini 3.5 Live Translate dari Google dan GPT Realtime Whisper dari OpenAI adalah dua model AI unggulan. Gemini 3.5 Live Translate menawarkan jendela konteks 131.1K token dengan harga $5.00/$20.00 per 1 juta token, sedangkan GPT Realtime Whisper menyediakan konteks 448 token seharga $0.01/$0.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Gemini 3.5 Live Translate
Model Suara & Audio AsliGemini 3.5 Live Translate dari Google adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 131K, kecepatan 130 token/detik, indeks kecerdasan 84/100, ser
$5.00 / 1M
$20.00 / 1M
131.1K tokens
N/A
GPT Realtime Whisper
Model Suara & Audio AsliGPT Realtime Whisper dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 0K, kecepatan 140 token/detik, indeks kecerdasan 44/100, serta tari
$0.01 / 1M
$0.00 / 1M
448 tokens
36%
Perbedaan Utama Sekilas
- GPT Realtime Whisper is 3000.0x cheaper for API usage (input + output tokens combined).
- Gemini 3.5 Live Translate has a larger context window (131K vs 0K tokens).
- GPT Realtime Whisper is faster at 140 tok/s vs 130 tok/s.
| Feature | Gemini 3.5 Live Translate | GPT Realtime Whisper |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 84 | 44 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $5.00 / 1M | $0.01 / 1M |
Output Price Cost per million output tokens | $20.00 / 1M | $0.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $3.70 / 1M | $0.00 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 448 tokens~1 A4 pages of text |
Max Output Tokens Per single request | 16K | 0K |
Throughput Speed Tokens generated per second | 130 tok/s | 140 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 36% |
GPQA Diamond Graduate-level reasoning | N/A | 46% |
Cached Input Price Prompt caching discount per 1M tokens | $1.00 / 1M | $0.00 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkEvaluations ongoing
Skor 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.
Gemini 3.5 Live Translate · Strengths & Key Advantages
- Jendela konteks 131K dengan kapasitas output maksimum hingga 16K token (Arena Elo 1420)
- Kecepatan generasi tinggi 130 token/detik dengan latensi token pertama (TTFT) hanya 300 ms
- Skema harga API kompetitif (tarif $5/$20 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
GPT Realtime Whisper · Strengths & Key Advantages
- Jendela konteks 0K dengan kapasitas output maksimum hingga 0K token (SWE-bench Verified 36% · GPQA Diamond 46%)
- Kecepatan generasi tinggi 140 token/detik dengan latensi token pertama (TTFT) hanya 150 ms
- Skema harga API kompetitif (tarif $0.006/$0 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 3.5 Live Translate | GPT Realtime Whisper |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.85 | $0.04 |
Output Tokens / Task Tokens generated per task | 8K | 3K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 3.5 Live Translate | GPT Realtime Whisper |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-3-5-live-translate | gpt-realtime-whisper |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-06 | 2026-05 |
| Knowledge Cutoff | February 2026 | February 2026 |
| Architecture | Low-latency neural speech-to-speech cross-lingual transformer | Streaming speech-to-text transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($5/1M in) across full 131K window | Flat rate ($0.006/1M in) across full 0K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $1/1M with configurable TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Text-only completion (No GUI action loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Prompt-based JSON extraction only |
| Web Search Grounding & Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Audio (~25–32 tokens/sec) | Text BPE (~4 chars/token) · Audio (~25–32 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 | Google DeepMind Frontier Safety Framework Verified | OpenAI Preparedness Framework Audited & System Card Published |
| 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 | audio | audio |
| Output Modalities | audio, text | text |
Gemini 3.5 Live Translate vs GPT Realtime Whisper: Jawaban Cepat (FAQ)
Which is more intelligent, Gemini 3.5 Live Translate or GPT Realtime Whisper?
Gemini 3.5 Live Translate is more intelligent. It scores 84 compared with 44 on the composite Intelligence Index.
Which model is faster?
GPT Realtime Whisper is faster, generating 140 tokens per second compared with 130 tokens per second.
Which model is cheaper to run?
GPT Realtime Whisper is cheaper at $0.00 per 1M tokens blended, compared with $3.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT Realtime Whisper has lower latency, with a time to first token of 0.15s compared with 0.30s.
Which model has a larger context window?
Gemini 3.5 Live Translate has a larger context window, supporting 131.1K tokens compared with 448 tokens.
Kesimpulan
Baik Gemini 3.5 Live Translate (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT Realtime Whisper (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Gemini 3.5 Live Translate unggul dalam penalaran dan pemrograman, GPT Realtime Whisper memberikan kecepatan generasi token lebih tinggi, dan GPT Realtime Whisper lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Gemini 3.5 Live Translate atau GPT Realtime Whisper?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Gemini 3.5 Live Translate memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Gemini 3.5 Live Translate vs GPT Realtime Whisper?+
Gemini 3.5 Live Translate mengenakan biaya $5.00 / $20.00 per 1M token input/output, sedangkan GPT Realtime Whisper sebesar $0.01 / $0.00. Secara keseluruhan, GPT Realtime Whisper lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Gemini 3.5 Live Translate mendukung konteks 131.1K token dibandingkan 448 token pada GPT Realtime Whisper, sementara GPT Realtime Whisper unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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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: Dokumentasi API resmi Google & OpenAI serta evaluasi benchmark independen (2026).