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Head-to-Head Model Comparison

GPT-Realtime-2.1 vs SeedRealtime

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
GPT-Realtime-2.1 vs SeedRealtime: Benchmarks, Pricing & Speed Comparison

GPT-Realtime-2.1 von OpenAI und SeedRealtime von ByteDance gehören zu den führenden KI-Modellen. GPT-Realtime-2.1 bietet ein Kontextfenster von 128K Tokens bei API-Preisen von $32.00/$64.00 pro 1M Tokens, während SeedRealtime 128K Tokens Kontext zu $0.50/$2.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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OpenAI

GPT-Realtime-2.1

Natives Sprach- & Audiomodell

GPT-Realtime-2.1 von OpenAI ist ein KI-Modell für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription mit 128K Kontextfenster, 90 Token/s Durchsatz, einem Intelligenz-Index von 65/100 und $32/$64 pro 1M Token.

Intelligence Index65 / 100
Input Token:

$32.00 / 1M

Output Token:

$64.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

62%

ByteDance

SeedRealtime

Natives Sprach- & Audiomodell

SeedRealtime von ByteDance ist ein KI-Modell für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription mit 128K Kontextfenster, 120 Token/s Durchsatz, einem Intelligenz-Index von 83/100 und $0.5/$2 pro 1M Token.

Intelligence Index83 / 100
Input Token:

$0.50 / 1M

Output Token:

$2.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Wichtigste Unterschiede auf einen Blick

  • SeedRealtime is 42.1x cheaper for API usage (input + output tokens combined).
  • SeedRealtime is faster at 120 tok/s vs 90 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-Realtime-2.1SeedRealtime
Intelligence Index
Composite reasoning & knowledge score (0-100)
6583
Provider
OpenAIByteDance
Input Price
Cost per million input tokens
$32.00 / 1M$0.50 / 1M
Output Price
Cost per million output tokens
$64.00 / 1M$2.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$15.04 / 1M$0.34 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
33K8K
Throughput Speed
Tokens generated per second
90 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
62%N/A
GPQA Diamond
Graduate-level reasoning
70%N/A
Cached Input Price
Prompt caching discount per 1M tokens
$3.20 / 1M$0.05 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
SeedRealtime
42.1x cheaper monthly runtime
Speed
SeedRealtime
+33% faster generation
Context
Tied
128K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

GPT-Realtime-2.1SeedRealtime
SWE-bench Verified (Autonomous Coding)

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

62%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

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

70%vsN/A
MMLU-Pro (Multi-task Language Understanding)

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

83%vs78.5%
LMSYS Chatbot Arena Elo

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

1350ptsvs1335pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

10.8%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

38%vsN/A
SciCode (Scientific Computing)

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

36.5%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

62%vsN/A
AIME (Advanced Math Competition)

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

86.5%vsN/A
Long-Context Reasoning

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

74%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs120 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
GPT-Realtime-2.10.32s
SeedRealtime0.28s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-Realtime-2.15.88s
SeedRealtime4.45s

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)
GPT-Realtime-2.1 Monthly API Bill
$110.40 / month
$32/1M in · $64/1M out
SeedRealtime Monthly API Bill
$2.63 / month
$0.5/1M in · $2/1M out
SeedRealtime saves approximately $107.78 / month (98%) under this workload.42.1x Savings

GPT-Realtime-2.1 · Strengths & Key Advantages

  • 128K Kontextfenster und bis zu 33K maximale Output-Token (SWE-bench Verified 62% · GPQA Diamond 70%)
  • Hohe Generierungsgeschwindigkeit von 90 Token/Sekunde bei nur 320 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($32/$64 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

SeedRealtime · Strengths & Key Advantages

  • 128K Kontextfenster und bis zu 8K maximale Output-Token (MMLU-Pro 78.5% · Arena Elo 1335)
  • Hohe Generierungsgeschwindigkeit von 120 Token/Sekunde bei nur 280 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($0.5/$2 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.

MetricGPT-Realtime-2.1SeedRealtime
Cost per Task
Estimated USD to finish one task
$6.66$0.12
Output Tokens / Task
Tokens generated per task
26K16K
Reasoning Tokens / Task
Thinking tokens burned per task
14K4K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-Realtime-2.1SeedRealtime
Official API Model ID (SDK)gpt-realtime-2-1seedrealtime
API ProtocolOpenAI Responses API & Chat Completions v1ByteDance REST API (OpenAI-Compatible)
Release Date2026-072026-08
Knowledge CutoffFebruary 2026June 2026
ArchitectureReal-time speech-to-speech multimodal transformerNative Audio-Visual Full-Duplex Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($32/1M in) across full 128K windowFlat rate ($0.5/1M in) across full 128K window
Prompt Cache Policy & TTLAutomatic prefix caching at $3.2/1M (no extra cache-write fee)Cached input at $0.05/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function callingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)API Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Audio (~25–32 tokens/sec)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · 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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedByteDance Production Safety & Alignment Verified
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 Modalitiesaudio, texttext, vision, audio
Output Modalitiesaudio, texttext, audio

GPT-Realtime-2.1 vs SeedRealtime: Schnelle Antworten (FAQ)

Which is more intelligent, GPT-Realtime-2.1 or SeedRealtime?

SeedRealtime is more intelligent. It scores 83 compared with 65 on the composite Intelligence Index.

Which model is faster?

SeedRealtime is faster, generating 120 tokens per second compared with 90 tokens per second.

Which model is cheaper to run?

SeedRealtime is cheaper at $0.34 per 1M tokens blended, compared with $15.04 (7:2:1 cache:input:output ratio).

Which model has lower latency?

SeedRealtime has lower latency, with a time to first token of 0.28s compared with 0.32s.

Fazit

Sowohl GPT-Realtime-2.1 (Optimal für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch SeedRealtime (Optimal für natürliche Sprachsynthese, Echtzeit-Audioverarbeitung und präzise Transkription, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: SeedRealtime führt bei komplexem Reasoning und Coding, SeedRealtime liefert den höheren Token-Durchsatz und SeedRealtime ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – GPT-Realtime-2.1 oder SeedRealtime?+

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

Wie unterscheiden sich die API-Preise von GPT-Realtime-2.1 und SeedRealtime?+

GPT-Realtime-2.1 kostet $32.00 / $64.00 pro 1M Input-/Output-Tokens, SeedRealtime liegt bei $0.50 / $2.00. Beim gewichteten Gesamtpreis ist SeedRealtime günstiger.

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

GPT-Realtime-2.1 bietet 128K Tokens Kontext gegenüber 128K Tokens bei SeedRealtime. Bei der Generierungsgeschwindigkeit liegt SeedRealtime 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 OpenAI und ByteDance, Systemkarten und unabhängige Benchmark-Auswertungen (2026).