Gemini Omni Flash vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Gemini Omni Flash by Google against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.
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Gemini Omni Flash
Omni de videorápido conversacional multimodal modelo capaz de generating y adapting short video clips interactively en el fly.
$2.00 / 1M
$15.00 / 1M
1.05M tokens
N/A
Claude Opus 5.5
Titán de inteligencia de fronterade Anthropic pinnacle modelo de frontera diseñado para de largo alcance agentic ingeniería de software, denso multimodal documento síntesis, y autónomo investigación flujos de trabajo.
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Diferencias Clave de un Vistazo
- Gemini Omni Flash is 1.4x cheaper for API usage (input + output tokens combined).
- Gemini Omni Flash has a larger context window (1M vs 1M tokens).
- Claude Opus 5.5 is faster at 78 tok/s vs 75 tok/s.
| Característica | Gemini Omni Flash | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 86 | 94 |
Provider | Anthropic | |
Input Price Cost per million input tokens | $2.00 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.25 / 1M | $3.08 / 1M |
Context Window Maximum input + output tokens | 1.05M tokens~1,573 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 33K | 128K |
Throughput Speed Tokens generated per second | 75 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 84.6% |
GPQA Diamond Graduate-level reasoning | N/A | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.50 / 1M | $0.40 / 1M |
¿Quién gana en cada área?
At-a-glance decision frameworkEvaluations ongoing
Puntuaciones 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.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini Omni Flash · Strengths & Key Advantages
- conversacional back-y-forth video editing
- 1M ventana de contexto para rich narrativo memoria
- rápido render speeds en comparación con traditional diffusion
Considerations & Trade-offs
- Disponibilidad de API en etapa de vista previa
- resolución capped un 1080p para transmisión speeds
Claude Opus 5.5 · Strengths & Key Advantages
- inigualable autónomo multipaso codificación agéntica y refactorización
- Flawless multidocumento razonamiento sobre 1M token contexto con no largo-prompt surcharge
- más alto Artificial análisis inteligencia Index ever measured (58/100), leading SWE-bench Pro un 89.9%
- Precise herramienta ejecución con robust error-recovery bucles
Considerations & Trade-offs
- Premium salida precios ($20.00/M) plus heavy razonamiento-token usage (~119K salida tokens por index tarea) keeps largo agentic se ejecuta expensive
- largo pensamiento times un maximum effort puede push un único hard agentic tarea toward ~$13
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini Omni Flash | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.50 | $3.85 |
Output Tokens / Task Tokens generated per task | 15K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 4K | 42K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Gemini Omni Flash | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-omni-flash | claude-opus-5-5-20260901 |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-06 | 2026-09 |
| Knowledge Cutoff | February 2026 | June 2026 |
| Architecture | Unified real-time text-to-video and conversational streaming engine | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.5/1M with configurable TTL | $0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| 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 | text, vision | text, vision |
| Output Modalities | video | text |
Gemini Omni Flash vs Claude Opus 5.5: Respuestas Rápidas (FAQ)
Which is more intelligent, Gemini Omni Flash or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 86 on the composite Intelligence Index.
Which model is faster?
Claude Opus 5.5 is faster, generating 78 tokens per second compared with 75 tokens per second.
Which model is cheaper to run?
Gemini Omni Flash is cheaper at $2.25 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini Omni Flash has lower latency, with a time to first token of 0.80s compared with 1.40s.
Which model has a larger context window?
Gemini Omni Flash has a larger context window, supporting 1.05M tokens compared with 1M tokens.
Veredicto
Choose Gemini Omni Flash for interactivo gaming, en tiempo real avatar response, y educational visual explanations, or choose Claude Opus 5.5 for grande-escala software development agentes, empresarial codebases, y de misión crítica científico síntesis.
Preguntas frecuentes
Which is cheaper: Gemini Omni Flash or Claude Opus 5.5?+
Gemini Omni Flash costs $2/1M input and $15/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.
Which model has a larger context window: Gemini Omni Flash or Claude Opus 5.5?+
Gemini Omni Flash supports 1.0M tokens whereas Claude Opus 5.5 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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Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: Google & Anthropic Official Documentation