Whisper Large v3 vs Gemini 3.5 Live Translate
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Whisper Large v3 dari OpenAI dan Gemini 3.5 Live Translate dari Google adalah dua model AI unggulan. Whisper Large v3 menawarkan jendela konteks 448 token dengan harga $0.01/$0.00 per 1 juta token, sedangkan Gemini 3.5 Live Translate menyediakan konteks 131.1K token seharga $5.00/$20.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Whisper Large v3
Model Suara & Audio AsliWhisper Large v3 dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 0K, kecepatan 55 token/detik, indeks kecerdasan 45/100, serta tarif $0.
$0.01 / 1M
$0.00 / 1M
448 tokens
36%
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
Perbedaan Utama Sekilas
- Whisper Large v3 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).
- Gemini 3.5 Live Translate is faster at 130 tok/s vs 55 tok/s.
| Feature | Whisper Large v3 | Gemini 3.5 Live Translate |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 45 | 84 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $0.01 / 1M | $5.00 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.00 / 1M | $3.70 / 1M |
Context Window Maximum input + output tokens | 448 tokens~1 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 0K | 16K |
Throughput Speed Tokens generated per second | 55 tok/s | 130 tok/s |
SWE-bench Verified Real-world software engineering | 36% | N/A |
GPQA Diamond Graduate-level reasoning | 46% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $1.00 / 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.
Whisper Large v3 · Strengths & Key Advantages
- Jendela konteks 0K dengan kapasitas output maksimum hingga 0K token (SWE-bench Verified 36% · GPQA Diamond 46%)
- Kecepatan generasi tinggi 55 token/detik dengan latensi token pertama (TTFT) hanya 350 ms
- Bobot terbuka (1.55B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Whisper Large v3 | Gemini 3.5 Live Translate |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.09 | $0.85 |
Output Tokens / Task Tokens generated per task | 3K | 8K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Whisper Large v3 | Gemini 3.5 Live Translate |
|---|---|---|
| Official API Model ID (SDK) | whisper-large-v3 | models/gemini-3-5-live-translate |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2023-11 | 2026-06 |
| Knowledge Cutoff | 2023 (audio corpus) | February 2026 |
| Architecture | Encoder-decoder speech transformer | Low-latency neural speech-to-speech cross-lingual transformer |
| Parameters | 1.55B | 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) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.006/1M in) across full 0K window | Flat rate ($5/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) | Implicit + Explicit Context Caching at $1/1M with configurable TTL |
| Computer Use / GUI Agent | Text-only completion (No GUI action loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Prompt-based JSON extraction only | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Vertex AI Supervised Adapter Tuning & Context Distillation |
| 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 | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | Google DeepMind Frontier Safety Framework Verified |
| 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 | audio | audio |
| Output Modalities | text | audio, text |
Whisper Large v3 vs Gemini 3.5 Live Translate: Jawaban Cepat (FAQ)
Which is more intelligent, Whisper Large v3 or Gemini 3.5 Live Translate?
Gemini 3.5 Live Translate is more intelligent. It scores 84 compared with 45 on the composite Intelligence Index.
Which model is faster?
Gemini 3.5 Live Translate is faster, generating 130 tokens per second compared with 55 tokens per second.
Which model is cheaper to run?
Whisper Large v3 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?
Gemini 3.5 Live Translate has lower latency, with a time to first token of 0.30s compared with 0.35s.
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 Whisper Large v3 (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun 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.) sangat tangguh: Gemini 3.5 Live Translate unggul dalam penalaran dan pemrograman, Gemini 3.5 Live Translate memberikan kecepatan generasi token lebih tinggi, dan Whisper Large v3 lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Whisper Large v3 atau Gemini 3.5 Live Translate?+
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 Whisper Large v3 vs Gemini 3.5 Live Translate?+
Whisper Large v3 mengenakan biaya $0.01 / $0.00 per 1M token input/output, sedangkan Gemini 3.5 Live Translate sebesar $5.00 / $20.00. Secara keseluruhan, Whisper Large v3 lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Whisper Large v3 mendukung konteks 448 token dibandingkan 131.1K token pada Gemini 3.5 Live Translate, sementara Gemini 3.5 Live Translate 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 OpenAI & Google serta evaluasi benchmark independen (2026).