Whisper Large v3 Turbo vs Whisper Large v3
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Whisper Large v3 Turbo dari OpenAI dan Whisper Large v3 dari OpenAI adalah dua model AI unggulan. Whisper Large v3 Turbo menawarkan jendela konteks 448 token dengan harga $0.00/$0.00 per 1 juta token, sedangkan Whisper Large v3 menyediakan konteks 448 token seharga $0.01/$0.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Whisper Large v3 Turbo
Model Suara & Audio AsliWhisper Large v3 Turbo dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 0K, kecepatan 180 token/detik, indeks kecerdasan 42/100, serta ta
$0.00 / 1M
$0.00 / 1M
448 tokens
36%
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%
Perbedaan Utama Sekilas
- Whisper Large v3 Turbo is 10.0x cheaper for API usage (input + output tokens combined).
- Whisper Large v3 Turbo is faster at 180 tok/s vs 55 tok/s.
- Whisper Large v3 leads on SWE-bench coding (36.0% vs 36.0%).
| Feature | Whisper Large v3 Turbo | Whisper Large v3 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 42 | 45 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $0.00 / 1M | $0.01 / 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 | 448 tokens~1 A4 pages of text | 448 tokens~1 A4 pages of text |
Max Output Tokens Per single request | 0K | 0K |
Throughput Speed Tokens generated per second | 180 tok/s | 55 tok/s |
SWE-bench Verified Real-world software engineering | 36% | 36% |
GPQA Diamond Graduate-level reasoning | 46% | 46% |
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.
Whisper Large v3 Turbo · Strengths & Key Advantages
- Jendela konteks 0K dengan kapasitas output maksimum hingga 0K token (SWE-bench Verified 36% · GPQA Diamond 46%)
- Kecepatan generasi tinggi 180 token/detik dengan latensi token pertama (TTFT) hanya 120 ms
- Bobot terbuka (809M) 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
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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Whisper Large v3 Turbo | Whisper Large v3 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.03 | $0.09 |
Output Tokens / Task Tokens generated per task | 3K | 3K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Whisper Large v3 Turbo | Whisper Large v3 |
|---|---|---|
| Official API Model ID (SDK) | whisper-large-v3-turbo | whisper-large-v3 |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-10 | 2023-11 |
| Knowledge Cutoff | 2024 (audio corpus) | 2023 (audio corpus) |
| Architecture | Distilled encoder-decoder speech transformer | Encoder-decoder speech transformer |
| Parameters | 809M | 1.55B |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.0006/1M in) across full 0K window | Flat rate ($0.006/1M in) across full 0K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) | Automatic prefix caching at $0/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Text-only completion (No GUI action loop) | Text-only completion (No GUI action loop) |
| MCP & Parallel Tool Calling | Prompt-based JSON extraction only | Prompt-based JSON extraction only |
| Web Search Grounding & Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG | 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) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| 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) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16) |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | audio | audio |
| Output Modalities | text | text |
Whisper Large v3 Turbo vs Whisper Large v3: Jawaban Cepat (FAQ)
Which is more intelligent, Whisper Large v3 Turbo or Whisper Large v3?
Whisper Large v3 is more intelligent. It scores 45 compared with 42 on the composite Intelligence Index.
Which model is faster?
Whisper Large v3 Turbo is faster, generating 180 tokens per second compared with 55 tokens per second.
Which model has lower latency?
Whisper Large v3 Turbo has lower latency, with a time to first token of 0.12s compared with 0.35s.
Kesimpulan
Baik Whisper Large v3 Turbo (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Whisper Large v3 (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Whisper Large v3 unggul dalam penalaran dan pemrograman, Whisper Large v3 Turbo memberikan kecepatan generasi token lebih tinggi, dan Whisper Large v3 Turbo lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Whisper Large v3 Turbo atau Whisper Large v3?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Whisper Large v3 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Whisper Large v3 Turbo vs Whisper Large v3?+
Whisper Large v3 Turbo mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan Whisper Large v3 sebesar $0.01 / $0.00. Secara keseluruhan, Whisper Large v3 Turbo lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Whisper Large v3 Turbo mendukung konteks 448 token dibandingkan 448 token pada Whisper Large v3, sementara Whisper Large v3 Turbo 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.
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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 & OpenAI serta evaluasi benchmark independen (2026).