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Claude Sonnet 5 vs Claude Sonnet 5.5

vs

Cuál usar y cuándo

claude-sonnet-5 y claude-sonnet-5-5 tienen un precio idéntico de $2 por millón de tokens de entrada, $10 por millón de salida y $0.2 en lecturas de caché, y ambos comparten un contexto de 1000000 tokens, una salida máxima de 128000, entrada de texto e imagen, y los mismos flags de chat, code, thinking, tools y reasoning. Las diferencias reales radican en la generación y el control: claude-sonnet-5-5 es el lanzamiento más reciente (2026-09-28, corte de conocimiento en 2026-06), mientras que claude-sonnet-5 (2026-06-30, corte en 2026-01) te permite desactivar thinking. Elige claude-sonnet-5 cuando necesites respuestas sin thinking; de lo contrario, usa claude-sonnet-5-5 por el corte de conocimiento más reciente sin costo adicional.

Benchmarks

Claude Sonnet 5.5: el proveedor no ha publicado resultados de benchmarks.

Sobre la mediaNinguno mejorClaude Sonnet 54 / 221 / 22
Claude Sonnet 5 Claude Sonnet 5.5 otros modelos medidos media de los modelos comparados ★ ningún otro modelo puntuó más alto
DeepSWE 1.1
53.8%
N/A
BioMysteryBench hard
34.1%
N/A
OSWorld 2.0 Partial score, batch tool enabled
42.6%
N/A
Finance Agent v2
53.9%
N/A
Harvey Lab-AA
90.1%
N/A
HLE-Verified
31%
N/A
AutomationBench
10.7%
N/A
LVBench
68.5%
N/A

Publicado por los proveedores: Alibaba (Qwen) Anthropic DeepSeek Google Moonshot OpenAI Tencent Z.ai

Precios

Claude Sonnet 5 Claude Sonnet 5.5 Δ
Entrada / 1M tokens $2 $2 =
Salida / 1M tokens $10 $10 =
Lectura de caché / 1M tokens $0.2 $0.2 =
Escritura en caché 1.25x (5m) / 2x (1h) 1.25x (5m) / 2x (1h) -

Tarifas del catálogo en vivo en el momento de la compilación; la página de cada modelo incluye la ficha actualizada.

Dónde se sitúan - precio de entrada por 1M de tokens en todos los 76 modelos de chat en esta unidad de facturación (escala logarítmica)

Capacidades

Claude Sonnet 5 Claude Sonnet 5.5
Uso de herramientas sí sí
Control de pensamiento configurable siempre activo
Salida estructurada sí sí
Caché de prompt explícito (marcas el prefijo) explícito (marcas el prefijo)
Tiempo de vida de la caché 5m default, 1h option 5m default, 1h option
Prefijo mínimo en caché 1024 tokens 1024 tokens

Especificaciones

Claude Sonnet 5 Claude Sonnet 5.5
Modalidades de entrada texto imagen texto imagen
Modalidades de salida texto texto
Lanzamiento 2026-06-30 2026-09-28
Límite de conocimiento 2026-01 2026-06
Ventana de contexto 1M 1M
Salida máxima 128K 128K
Parámetro de pensamiento
  • thinking.type "adaptive"
  • output_config.effort
thinking.type
Valores aceptados
thinking.type
  • adaptive
  • disabled
effort
  • low
  • medium
  • high
  • xhigh
  • max

"enabled" returns 400

thinking.type
  • adaptive (default)
  • between_tools
Predeterminado

thinking on (adaptive)

effort
  • high
adaptive, effort high

Las especificaciones se transcriben de la documentación de cada proveedor; si un proveedor no publica una fila, se omite en lugar de inferirse. Fuentes completas: Claude Sonnet 5 · Claude Sonnet 5.5

Un prompt, ambos modelos - medido a través del gateway

PROMPT Explain to a CFO, in exactly three sentences, why our LLM bill doubled after we enabled reasoning. COMPROBAR exactamente 3 frases

Claude Sonnet 5 superado · 3 sentences

Reasoning mode works by having the model generate extended internal "thinking" steps before producing its final answer, and since we're billed on total tokens, that hidden reasoning text adds significantly to what we pay for—even though you never see it in the output. This is different from simply getting longer visible responses; the model is essentially "showing its work" behind the scenes, and complex prompts can trigger thousands of extra reasoning tokens per request. The upside is improved accuracy on complex tasks, but if we want to control costs, we should selectively enable reasoning only for queries that truly need it, rather than applying it universally.

salida 194 tok latencia 4.3 s

Claude Sonnet 5.5 superado · 3 sentences

Enabling reasoning makes the model "think" before it answers, and that internal thinking is generated as extra text (reasoning tokens) that we are billed for at the same rate as output tokens, even though users never see it. Output tokens also cost several times more than input tokens, so a single request that used to produce a short answer can now generate many times more billable text behind the scenes. Because our request volume and prompts didn't change, the doubling comes almost entirely from this hidden thinking, and we can bring it down by limiting reasoning effort, turning it off for simple tasks, and reserving it for the workloads where the accuracy gain justifies the cost.

salida 205 tok latencia 3.6 s

Seguimiento de la instrucción (exactamente tres frases - contables), adaptación a la audiencia (registro de CFO), y la brecha de facturación por pensamiento oculto que los medidores de tokens de abajo dejan ver.

PROMPT This function is supposed to return the longest run of consecutive equal items, but callers report it is off by one on single-element inputs and misses runs that end at the last index. Fix it and explain the bug in one paragraph. COMPROBAR el arreglo pasa las pruebas

Claude Sonnet 5 superado · 8/8 cases

## The Bug The function has two related off-by-one issues rooted in the same cause: `cur` and `best` are initialized to `0` instead of `1`, treating run lengths as the number of *matches* between adjacent elements rather than the number of *elements* in the run. This means a single-element input never enters the loop (since `range(1, 1)` is empty) and returns `0` instead of the correct answer of `1`. It also means that for any input, the run length is undercounted by exactly one — a run of 3 equal elements only produces 2 "match" increments, so `best` ends up as 2 instead of 3. The claim that it "misses runs that end at the last index" is actually a symptom of this same undercount: the logic does update `best` correctly on every iteration (including the last), but because it's counting matches instead of elements, the final reported value is always one less than the true longest run. […]

salida 536 tok latencia 7.1 s

Claude Sonnet 5.5 superado · 8/8 cases

**The bug:** `cur` counts the number of *adjacent equal pairs* rather than the number of items in the run. A run of length k contains only k−1 such pairs, so every result is one too small. The counter also starts at 0 and the loop starts at index 1, so a single-element list never updates `best` and returns 0 instead of 1. (An empty list should return 0.) In addition, `cur` resets to 0 on a mismatch, when it should reset to 1, because the item at `xs[i]` begins a new run of length 1. The claim that it "misses runs ending at the last index" is really the same off-by-one: the final run is counted, but as one less than its true length. Because `best` is updated inside the loop on every extension, the last run isn't skipped. […]

salida 444 tok latencia 6.7 s

Si el arreglo es realmente correcto (ejecutable), la densidad de la explicación, y la eficiencia en tokens sobre una tarea acotada.

PROMPT Extract a JSON object with fields {company, quarter, revenue_usd_m, growth_pct, guidance} from this text. Use null for anything not stated; add no other fields. COMPROBAR JSON válido, esquema exacto

Claude Sonnet 5 superado · 5/5 fields, guidance null

```json { "company": "Meridian Robotics", "quarter": "Q3", "revenue_usd_m": 412, "growth_pct": 11.5, "guidance": null } ```

salida 348 tok latencia 5.3 s

Claude Sonnet 5.5 superado · 5/5 fields, guidance null

Here is the extracted JSON: ```json { "company": "Meridian Robotics", "quarter": "September quarter", "revenue_usd_m": 412, "growth_pct": 11, "guidance": null } ``` Notes on the choices: - **quarter**: The text says "September quarter" without specifying a fiscal year or Q-number, so I kept the wording as stated. - **revenue_usd_m**: The text gives "412" for the topline, with no currency or unit stated explicitly. I've taken it as 412 million USD per the field definition, but the text does not confirm that, and the figure is constant-currency. - **growth_pct**: "Eleven and change" means slightly above 11, so 11 is an approximation. The exact figure isn't given. - **guidance**: Guidance is withheld pending the Q4 close, so no guidance is stated, hence null.

salida 300 tok latencia 3.5 s

Obediencia al esquema (sin campos inventados), presión de alucinación (guidance se retiene explícitamente), y diferencias en la ruta de salida estructurada.

PROMPT Write a 120-word product announcement for an API gateway feature that caches prompts across providers. Forbidden words: "seamless", "unlock", "game-changer", "revolutionize", "empower". Exactly one sentence must be a question. COMPROBAR 120 palabras, 0 palabras prohibidas

Claude Sonnet 5 superado · 123 words, 0 banned, 1 question

## Introducing Cross-Provider Prompt Caching We're rolling out a new caching layer for our API gateway that works across every major LLM provider you connect through it. Instead of resending identical prompts and paying full price each time, the gateway recognizes repeated requests and serves cached responses in milliseconds—regardless of whether you're routing to OpenAI, Anthropic, or Google. What does this mean for your bill and your latency? Both drop, often significantly, especially for teams running high-volume, repetitive workloads like customer support bots or batch content generation. The cache is configurable per route, with adjustable TTLs and invalidation rules, so you stay in control of freshness versus cost. Available now for all Pro and Enterprise plans. Check your dashboard to enable it today.

salida 259 tok latencia 4.8 s

Claude Sonnet 5.5 superado · 122 words, 0 banned, 1 question

**Introducing Cross-Provider Prompt Caching** Your API gateway now caches prompts across every connected LLM provider, whether you route traffic to OpenAI, Anthropic, Google, or a self-hosted model. Here's how it works: the gateway fingerprints each prompt prefix, stores it centrally, and applies the right provider-specific caching mechanism automatically. When you switch providers or fail over during an outage, your cached context follows you. Early testing shows input token costs dropping by up to 70% on repeated system prompts and long documents, with latency improvements of 40% or more on cache hits. Tired of paying to send the same instructions thousands of times a day? Enable it with one configuration flag. Cache rules, TTLs, and per-team isolation are available in the dashboard today.

salida 266 tok latencia 3.8 s

Obediencia a las restricciones (presupuesto de palabras, lista de palabras prohibidas, la única pregunta), huella de estilo, y control de la longitud.

Cambia entre ellos con una línea

Ambos IDs están en cada pestaña a continuación - el par de líneas resaltadas es la única edición. Mismo endpoint, misma clave, misma estructura de solicitud.

from openai import OpenAI

client = OpenAI(
    base_url="https://synthorai.io/v1",
    api_key="sk-syn-...",
)

resp = client.chat.completions.create(
    model="claude-sonnet-5",
    # model="claude-sonnet-5-5",  # descomenta esta línea, comenta la de arriba
    messages=[{"role": "user", "content": "Summarize this diff"}],
    reasoning_effort="medium",
)
print(resp.choices[0].message.content)

Obtén tu clave API →

Preguntas frecuentes

¿Cuál es más barato, Claude Sonnet 5 o Claude Sonnet 5.5?

Muestran el mismo entrada / 1m tokens ($2), por lo que el precio no es el factor decisivo en este caso - vea las especificaciones y capacidades a continuación.

¿Puedo hacer pruebas A/B de Claude Sonnet 5 frente a Claude Sonnet 5.5 sin dos integraciones?

Sí. Ambos se sirven a través del mismo endpoint compatible con OpenAI con una clave API - el cambio es una modificación de una línea en la cadena del modelo, por lo que puede enrutar una fracción del tráfico a cada uno y comparar las facturas directamente.

¿Admiten Claude Sonnet 5 y Claude Sonnet 5.5 caché de prompts?

Sí - ambos cobran las lecturas en caché por debajo de su tarifa de entrada, por lo que las cargas de trabajo con prefijo caliente cuestan menos de lo que sugieren las tarifas de lista. Las filas exactas de lectura en caché están en la tabla de precios de arriba.

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