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 di Google e GPT Realtime Whisper di OpenAI sono due modelli di IA di riferimento. Gemini 3.5 Live Translate offre una finestra di contesto di 131.1K token a $5.00/$20.00 per milione di token, mentre GPT Realtime Whisper mette a disposizione 448 token di contesto a $0.01/$0.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
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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
GPT Realtime Whisper
Modello Vocale e Audio NativoGPT Realtime Whisper 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 140 token/s, indice di intelligenza di 44/100 e
$0.01 / 1M
$0.00 / 1M
448 tokens
36%
Differenze Chiave a Colpo d’Occhio
- 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 |
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.
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
GPT Realtime Whisper · 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 140 token/secondo con latenza al primo token (TTFT) di soli 150 ms
- Economia API competitiva ($0.006/$0 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
- Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità
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 |
Specifiche Tecniche
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: Risposte Rapide (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.
Verdetto
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.) sia GPT Realtime Whisper (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, GPT Realtime Whisper garantisce una generazione più rapida e GPT Realtime Whisper offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, Gemini 3.5 Live Translate o GPT Realtime Whisper?+
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 Gemini 3.5 Live Translate e GPT Realtime Whisper?+
Gemini 3.5 Live Translate costa $5.00 / $20.00 per milione di token di input/output, mentre GPT Realtime Whisper costa $0.01 / $0.00. Nel costo combinato, GPT Realtime Whisper risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
Gemini 3.5 Live Translate supporta 131.1K token di contesto contro 448 token di GPT Realtime Whisper, mentre GPT Realtime Whisper 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.
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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 Google e OpenAI, schede di sistema e benchmark indipendenti (2026).