Whisper Large v3 Turbo vs Whisper Large v3
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Whisper Large v3 Turbo by OpenAI and Whisper Large v3 by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Whisper Large v3 Turbo holds a notable pricing advantage for token ingestion. On output generation, costs are matched. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 448 tokens. In latency-sensitive production environments, Whisper Large v3 Turbo leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Whisper Large v3 Turbo
Modello a Pesi ApertiWhisper Large v3 Turbo di OpenAI è un modello di intelligenza artificiale con finestra di contesto da 448 token e tariffazione API di $0.0006/1M token in input e $0/1M in output, ideale per coding, ragionamento e automazione aziendale.
$0.00 / 1M
$0.00 / 1M
448 tokens
36%
Whisper Large v3
Modello a Pesi ApertiWhisper Large v3 di OpenAI è un modello di intelligenza artificiale con finestra di contesto da 448 token e tariffazione API di $0.006/1M token in input e $0/1M in output, ideale per coding, ragionamento e automazione aziendale.
$0.01 / 1M
$0.00 / 1M
448 tokens
36%
Differenze Chiave a Colpo d’Occhio
- 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% |
Chi vince in ogni categoria?
At-a-glance decision frameworkPunteggi Benchmark Verificati
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.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Whisper Large v3 Turbo · Strengths & Key Advantages
- Architettura Distilled encoder-decoder speech transformer avanzata di OpenAI con supporto fino a 448 token di contesto
- Ottimo rapporto qualità-prezzo ($0.0006/1M input, $0/1M output) e bassa latenza
- Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
- L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
- Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato
Whisper Large v3 · Strengths & Key Advantages
- Architettura Encoder-decoder speech transformer avanzata di OpenAI con supporto fino a 448 token di contesto
- Ottimo rapporto qualità-prezzo ($0.006/1M input, $0/1M output) e bassa latenza
- Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
- L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
- Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato
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 |
Specifiche Tecniche
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: Risposte Rapide (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.
Verdetto
Verdict & Model Selection Recommendation: Choose Whisper Large v3 Turbo if your priority is Fast, cheap transcription at scale. Its performance in demanding tasks justifies its operational token cost. Choose Whisper Large v3 if your workflow prioritizes Batch transcription, subtitling and multilingual captioning. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Domande Frequenti (FAQ)
How does Whisper Large v3 Turbo compare to Whisper Large v3 in API token pricing and cost per token?+
Whisper Large v3 Turbo costs $0.00 per 1M input tokens and $0.00 per 1M output tokens, whereas Whisper Large v3 costs $0.01 input and $0.00 output. Overall, Whisper Large v3 Turbo is the more cost-effective model for high-volume API pipelines.
Which model has a larger context window: Whisper Large v3 Turbo or Whisper Large v3?+
Both Whisper Large v3 Turbo and Whisper Large v3 offer an identical context window of 448 tokens (~336 words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: Whisper Large v3 Turbo or Whisper Large v3?+
Both models achieve an identical 36% score on SWE-bench Verified, demonstrating matched software engineering capabilities.
What is the difference in reasoning capability and extended thinking between Whisper Large v3 Turbo and Whisper Large v3?+
Whisper Large v3 Turbo is optimized for low-latency direct generation. In contrast, Whisper Large v3 focuses on standard fast inference.
How does inference speed (tokens per second) compare between Whisper Large v3 Turbo and Whisper Large v3?+
Whisper Large v3 Turbo generates approximately 180 tokens per second, while Whisper Large v3 delivers 55 tokens per second. In latency-sensitive production environments, Whisper Large v3 Turbo provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Whisper Large v3 Turbo and Whisper Large v3 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Whisper Large v3 Turbo to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Whisper Large v3. This tiered routing pattern cuts overall API bills by up to 70%.
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.
Fonti ufficiali: GetInfoUs Independent AI Benchmarks & Official API Specs