Whisper Large v3 Turbo vs Gemini 3.5 Live Translate
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Whisper Large v3 Turbo di OpenAI e Gemini 3.5 Live Translate di Google sono due modelli di IA di riferimento. Whisper Large v3 Turbo offre una finestra di contesto di 448 token a $0.00/$0.00 per milione di token, mentre Gemini 3.5 Live Translate mette a disposizione 131.1K token di contesto a $5.00/$20.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
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Whisper Large v3 Turbo
Modello Vocale e Audio NativoWhisper Large v3 Turbo di OpenAI è un modello di IA progettato per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, con finestra di contesto da 0K, velocità di 180 token/s, indice di intelligenza di 42/100
$0.00 / 1M
$0.00 / 1M
448 tokens
36%
Gemini 3.5 Live Translate
Modello Vocale e Audio NativoGemini 3.5 Live Translate di Google è un modello di IA progettato per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, con finestra di contesto da 131K, velocità di 130 token/s, indice di intelligenza di 84
$5.00 / 1M
$20.00 / 1M
131.1K tokens
N/A
Differenze Chiave a Colpo d’Occhio
- Whisper Large v3 Turbo is 30000.0x cheaper for API usage (input + output tokens combined).
- Gemini 3.5 Live Translate has a larger context window (131K vs 0K tokens).
- Whisper Large v3 Turbo is faster at 180 tok/s vs 130 tok/s.
| Feature | Whisper Large v3 Turbo | Gemini 3.5 Live Translate |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 42 | 84 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $0.00 / 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 | 180 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 |
Chi vince in ogni categoria?
At-a-glance decision frameworkEvaluations ongoing
Punteggi 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
- Finestra di contesto da 0K con capacità massima di output fino a 0K token (SWE-bench Verified 36% · GPQA Diamond 46%)
- Throughput elevato di 180 token/secondo con latenza al primo token (TTFT) di soli 120 ms
- Pesi aperti (809M) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
- Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
- Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità
Gemini 3.5 Live Translate · Strengths & Key Advantages
- Finestra di contesto da 131K con capacità massima di output fino a 16K token (Arena Elo 1420)
- Throughput elevato di 130 token/secondo con latenza al primo token (TTFT) di soli 300 ms
- Economia API competitiva ($5/$20 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
- Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
- Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Whisper Large v3 Turbo | Gemini 3.5 Live Translate |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.03 | $0.85 |
Output Tokens / Task Tokens generated per task | 3K | 8K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Whisper Large v3 Turbo | Gemini 3.5 Live Translate |
|---|---|---|
| Official API Model ID (SDK) | whisper-large-v3-turbo | models/gemini-3-5-live-translate |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2024-10 | 2026-06 |
| Knowledge Cutoff | 2024 (audio corpus) | February 2026 |
| Architecture | Distilled encoder-decoder speech transformer | Low-latency neural speech-to-speech cross-lingual transformer |
| Parameters | 809M | 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 ($0.0006/1M 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 Turbo vs Gemini 3.5 Live Translate: Risposte Rapide (FAQ)
Which is more intelligent, Whisper Large v3 Turbo or Gemini 3.5 Live Translate?
Gemini 3.5 Live Translate is more intelligent. It scores 84 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 130 tokens per second.
Which model is cheaper to run?
Whisper Large v3 Turbo 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?
Whisper Large v3 Turbo has lower latency, with a time to first token of 0.12s 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.
Verdetto
Sia Whisper Large v3 Turbo (Ideale per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, sistemi RAG aziendali e integrazioni API scalabili.) sia Gemini 3.5 Live Translate (Ideale per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Gemini 3.5 Live Translate guida nei benchmark di ragionamento e programmazione, Whisper Large v3 Turbo garantisce una generazione più rapida e Whisper Large v3 Turbo offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, Whisper Large v3 Turbo o Gemini 3.5 Live Translate?+
Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Gemini 3.5 Live Translate. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.
Qual è la differenza di prezzo API tra Whisper Large v3 Turbo e Gemini 3.5 Live Translate?+
Whisper Large v3 Turbo costa $0.00 / $0.00 per milione di token di input/output, mentre Gemini 3.5 Live Translate costa $5.00 / $20.00. Nel costo combinato, Whisper Large v3 Turbo risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
Whisper Large v3 Turbo supporta 448 token di contesto contro 131.1K token di Gemini 3.5 Live Translate, mentre Whisper Large v3 Turbo offre una velocità di generazione superiore.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Gemini 3.5 Live Translate vs GPT Realtime Whisper: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- GPT Realtime Whisper vs Whisper Large v3 Turbo: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- Whisper Large v3 Turbo vs Whisper Large v3: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- Whisper Large v3 vs Gemini 3.5 Live Translate: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
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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: Documentazione API ufficiale di OpenAI e Google, schede di sistema e benchmark indipendenti (2026).