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Gemini 3.5 Live Translate vs GPT Realtime Whisper

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Gemini 3.5 Live Translate vs GPT Realtime Whisper: Benchmarks, Pricing & Speed Comparison

Gemini 3.5 Live Translate von Google und GPT Realtime Whisper von OpenAI gehören zu den führenden KI-Modellen. Gemini 3.5 Live Translate bietet ein Kontextfenster von 131.1K Tokens bei API-Preisen von $5.00/$20.00 pro 1M Tokens, während GPT Realtime Whisper 448 Tokens Kontext zu $0.01/$0.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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Google

Gemini 3.5 Live Translate

Natives Sprach- & Audiomodell

Gemini 3.5 Live Translate von Google ist ein KI-Modell für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription mit 131K Kontextfenster, 130 Token/s Durchsatz, einem Intelligenz-Index von 84/100 und $5/$20 pro 1M

Intelligence Index84 / 100
Input Token:

$5.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

N/A

OpenAI

GPT Realtime Whisper

Natives Sprach- & Audiomodell

GPT Realtime Whisper von OpenAI ist ein KI-Modell für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription mit 0K Kontextfenster, 140 Token/s Durchsatz, einem Intelligenz-Index von 44/100 und $0.006/$0 pro 1M Toke

Intelligence Index44 / 100
Input Token:

$0.01 / 1M

Output Token:

$0.00 / 1M

Context Window:

448 tokens

SWE-bench Verified:

36%

Wichtigste Unterschiede auf einen Blick

  • 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.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 3.5 Live TranslateGPT Realtime Whisper
Intelligence Index
Composite reasoning & knowledge score (0-100)
8444
Provider
GoogleOpenAI
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 text448 tokens~1 A4 pages of text
Max Output Tokens
Per single request
16K0K
Throughput Speed
Tokens generated per second
130 tok/s140 tok/s
SWE-bench Verified
Real-world software engineering
N/A36%
GPQA Diamond
Graduate-level reasoning
N/A46%
Cached Input Price
Prompt caching discount per 1M tokens
$1.00 / 1M$0.00 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
GPT Realtime Whisper
3000.0x cheaper monthly runtime
Speed
GPT Realtime Whisper
+8% faster generation
Context
Gemini 3.5 Live Translate
131.1K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

Official evaluation metrics verified by independent third-party research labs.

Gemini 3.5 Live TranslateGPT Realtime Whisper
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

N/Avs36%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

N/Avs46%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

N/Avs66%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1420ptsvs1255pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs5.5%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs23%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs24.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs39%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs46%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs61%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs140 tok/s

Latenz & Antwortzeit

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Gemini 3.5 Live Translate0.30s
GPT Realtime Whisper0.15s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 3.5 Live Translate4.15s
GPT Realtime Whisper3.72s

Interaktiver Token-Kosten-Simulator

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Gemini 3.5 Live Translate Monthly API Bill
$27.00 / month
$5/1M in · $20/1M out
GPT Realtime Whisper Monthly API Bill
$0.01 / month
$0.006/1M in · $0/1M out
GPT Realtime Whisper saves approximately $26.99 / month (100%) under this workload.3000.0x Savings

Gemini 3.5 Live Translate · Strengths & Key Advantages

  • 131K Kontextfenster und bis zu 16K maximale Output-Token (Arena Elo 1420)
  • Hohe Generierungsgeschwindigkeit von 130 Token/Sekunde bei nur 300 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($5/$20 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
  • Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
  • Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung

GPT Realtime Whisper · Strengths & Key Advantages

  • 0K Kontextfenster und bis zu 0K maximale Output-Token (SWE-bench Verified 36% · GPQA Diamond 46%)
  • Hohe Generierungsgeschwindigkeit von 140 Token/Sekunde bei nur 150 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($0.006/$0 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
  • Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
  • Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGemini 3.5 Live TranslateGPT Realtime Whisper
Cost per Task
Estimated USD to finish one task
$0.85$0.04
Output Tokens / Task
Tokens generated per task
8K3K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 3.5 Live TranslateGPT Realtime Whisper
Official API Model ID (SDK)models/gemini-3-5-live-translategpt-realtime-whisper
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKOpenAI Responses API & Chat Completions v1
Release Date2026-062026-05
Knowledge CutoffFebruary 2026February 2026
ArchitectureLow-latency neural speech-to-speech cross-lingual transformerStreaming speech-to-text transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 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 windowFlat rate ($0.006/1M in) across full 0K window
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $1/1M with configurable TTLAutomatic prefix caching at $0/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Text-only completion (No GUI action loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaPrompt-based JSON extraction only
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Audio (~25–32 tokens/sec)Text BPE (~4 chars/token) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAMCloud-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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiesaudioaudio
Output Modalitiesaudio, texttext

Gemini 3.5 Live Translate vs GPT Realtime Whisper: Schnelle Antworten (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.

Fazit

Sowohl Gemini 3.5 Live Translate (Optimal für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch GPT Realtime Whisper (Optimal für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Gemini 3.5 Live Translate führt bei komplexem Reasoning und Coding, GPT Realtime Whisper liefert den höheren Token-Durchsatz und GPT Realtime Whisper ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Gemini 3.5 Live Translate oder GPT Realtime Whisper?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Gemini 3.5 Live Translate vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Gemini 3.5 Live Translate und GPT Realtime Whisper?+

Gemini 3.5 Live Translate kostet $5.00 / $20.00 pro 1M Input-/Output-Tokens, GPT Realtime Whisper liegt bei $0.01 / $0.00. Beim gewichteten Gesamtpreis ist GPT Realtime Whisper günstiger.

Welches Modell hat das größere Kontextfenster und die höhere Geschwindigkeit?+

Gemini 3.5 Live Translate bietet 131.1K Tokens Kontext gegenüber 448 Tokens bei GPT Realtime Whisper. Bei der Generierungsgeschwindigkeit liegt GPT Realtime Whisper vorn.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

Offizielle Quellen: Offizielle API-Dokumentation von Google und OpenAI, Systemkarten und unabhängige Benchmark-Auswertungen (2026).