Whisper Large v3 Turbo vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Whisper Large v3 Turbo by OpenAI against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.
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Whisper Large v3 Turbo
Modelo Nativo de Voz e ÁudioO Whisper Large v3 Turbo da OpenAI é um modelo de IA projetado para síntese de voz natural, transcrição de áudio e interação falada em tempo real, oferecendo janela de contexto de 0K, velocidade de 180 tokens/s, índice de inteligência de 42
$0.00 / 1M
$0.00 / 1M
448 tokens
36%
Gemini 4 Argon
IA Multimodal NativaO Gemini 4 Argon da Google é um modelo de IA projetado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, oferecendo janela de contexto de 1M, velocidade de 115 tokens/s, índice de inteligência de 97/100 e
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Principais Diferenças em Resumo
- Whisper Large v3 Turbo is 13500.0x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon has a larger context window (1M vs 0K tokens).
- Whisper Large v3 Turbo is faster at 180 tok/s vs 115 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 36.0%).
| Feature | Whisper Large v3 Turbo | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 42 | 97 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $0.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.00 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 448 tokens~1 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 0K | 1000K |
Throughput Speed Tokens generated per second | 180 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 36% | 81.9% |
GPQA Diamond Graduate-level reasoning | 46% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.10 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkPontuações de Benchmarks Verificadas
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.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Whisper Large v3 Turbo · Strengths & Key Advantages
- Janela de contexto de 0K com limite máximo de saída de 0K tokens (SWE-bench Verified 36% · GPQA Diamond 46%)
- Taxa de transferência rápida de 180 tokens/segundo com latência inicial (TTFT) de 120 ms
- Pesos abertos (809M) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama
Considerations & Trade-offs
- Requer servidores GPU com memória VRAM adequada para execução local em precisão total
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
Gemini 4 Argon · Strengths & Key Advantages
- Janela de contexto de 1M com limite máximo de saída de 1M tokens (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
- Taxa de transferência rápida de 115 tokens/segundo com latência inicial (TTFT) de 850 ms
- Economia de API competitiva ($2/$10 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Whisper Large v3 Turbo | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.03 | $2.45 |
Output Tokens / Task Tokens generated per task | 3K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Whisper Large v3 Turbo | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | whisper-large-v3-turbo | models/gemini-4-argon |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2024-10 | 2026-09 |
| Knowledge Cutoff | 2024 (audio corpus) | June 2026 |
| Architecture | Distilled encoder-decoder speech transformer | Pathways Multimodal Sparse Mixture-of-Experts |
| 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) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.0006/1M in) across full 0K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL |
| Computer Use / GUI Agent | Text-only completion (No GUI action loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 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 | text, vision, audio, video |
| Output Modalities | text | text |
Whisper Large v3 Turbo vs Gemini 4 Argon: Respostas Rápidas (FAQ)
Which is more intelligent, Whisper Large v3 Turbo or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 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 115 tokens per second.
Which model is cheaper to run?
Whisper Large v3 Turbo is cheaper at $0.00 per 1M tokens blended, compared with $1.47 (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 0.85s.
Which model has a larger context window?
Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 448 tokens.
Veredito
Choose Whisper Large v3 Turbo for indicado para síntese de voz natural, transcrição de áudio e interação falada em tempo real, arquiteturas rag corporativas e integração escalável via api., or choose Gemini 4 Argon for indicado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, arquiteturas rag corporativas e integração escalável via api..
Perguntas Frequentes (FAQ)
Which is cheaper: Whisper Large v3 Turbo or Gemini 4 Argon?+
Whisper Large v3 Turbo costs $0.0006/1M input and $0/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Whisper Large v3 Turbo or Gemini 4 Argon?+
Whisper Large v3 Turbo supports 0K tokens whereas Gemini 4 Argon supports 1M tokens.
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.
Fontes oficiais: OpenAI & Google Official Documentation