Head-to-Head Model Comparison

GPT-6 Sol vs Aya Expanse 32B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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Compare GPT-6 Sol by OpenAI against Aya Expanse 32B by Cohere across real-world coding, reasoning, token economics, and latency.

Comparación Directa (VS)

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GPT-6 Sol

GPT-6 rentable

un GPT-6 nivel ofreciendo complejo codificación y profesional trabajo un half el precio de GPT-5.6 Sol.

Intelligence Index93 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.1%

Cohere

Aya Expanse 32B

Multilingüe de 32B

alto-capacidad 32B multilingüe modelo ofreciendo superior rendimiento un través de 23 global idiomas con rich matiz y 128K contexto.

Intelligence Index44 / 100
Input Token:

$0.25 / 1M

Output Token:

$0.50 / 1M

Context Window:

128K tokens

SWE-bench Verified:

33.5%

Diferencias Clave de un Vistazo

  • Aya Expanse 32B is 13.3x cheaper for API usage (input + output tokens combined).
  • GPT-6 Sol has a larger context window (1M vs 128K tokens).
  • GPT-6 Sol is faster at 116 tok/s vs 85 tok/s.
  • GPT-6 Sol leads on SWE-bench coding (82.1% vs 33.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaGPT-6 SolAya Expanse 32B
Intelligence Index
Composite reasoning & knowledge score (0-100)
9344
Provider
OpenAICohere
Input Price
Cost per million input tokens
$2.00 / 1M$0.25 / 1M
Output Price
Cost per million output tokens
$10.00 / 1M$0.50 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.47 / 1M$0.14 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
128K8K
Throughput Speed
Tokens generated per second
116 tok/s85 tok/s
SWE-bench Verified
Real-world software engineering
82.1%33.5%
GPQA Diamond
Graduate-level reasoning
80.6%50%
Cached Input Price
Prompt caching discount per 1M tokens
$0.10 / 1M$0.06 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
GPT-6 Sol
+48.6% SWE-bench lead
Costo
Aya Expanse 32B
13.3x cheaper monthly runtime
Velocidad
GPT-6 Sol
+36% faster generation
Contexto
GPT-6 Sol
1M tokens window

Puntuaciones de Benchmarks Verificadas

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

GPT-6 SolAya Expanse 32B
SWE-bench Verified (Autonomous Coding)

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

82.1%vs33.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

80.6%vs50%
MMLU-Pro (Multi-task Language Understanding)

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

89.8%vs73%
LMSYS Chatbot Arena Elo

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

1516ptsvs1265pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

18%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

63.2%vsN/A
SciCode (Scientific Computing)

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

54.5%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

79.5%vsN/A
AIME (Advanced Math Competition)

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

93.4%vsN/A
Long-Context Reasoning

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

90.8%vs72%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

116 tok/s vs85 tok/s

Latencia y Tiempo de Respuesta

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-6 Sol1.16s
Aya Expanse 32B0.44s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-6 Sol5.47s
Aya Expanse 32B6.32s

Simulador Interactivo de Costos de Tokens

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-6 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Aya Expanse 32B Monthly API Bill
$0.92 / month
$0.25/1M in · $0.5/1M out
Aya Expanse 32B saves approximately $11.23 / month (92%) under this workload.13.3x Savings

GPT-6 Sol · Strengths & Key Advantages

  • Roughly 50% cheaper que GPT-5.6 Sol
  • Error rate close un half del previous generación
  • sólido codificación agéntica y profesional flujos de trabajo
  • Roughly half el precio de GPT-5.6 Sol con mejor error rates
Considerations & Trade-offs
  • Weaker que GPT-6 Astra en el hardest tareas
  • Sits close en precio un GPT-6.1 Sol, which es stronger

Aya Expanse 32B · Strengths & Key Advantages

  • Substantially mayor razonamiento y factual precisión en non-English idiomas
  • Generous 128K ventana de contexto para largo multilingüe documento traducción
  • de pesos abiertos bajo permissive license para global researchers y enterprises
Considerations & Trade-offs
  • Slightly menor codificación pruebas de rendimiento que English-centric 32B peers
  • requiere sustancial GPU VRAM para multiturno local servicio

Token Use & Task Economics

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

MetricGPT-6 SolAya Expanse 32B
Cost per Task
Estimated USD to finish one task
$2.00$0.18
Output Tokens / Task
Tokens generated per task
62K28K
Reasoning Tokens / Task
Thinking tokens burned per task
36K0K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaGPT-6 SolAya Expanse 32B
Official API Model ID (SDK)gpt-6-solaya-expanse-32b
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-092024-10
Knowledge CutoffApril 2026August 2024
ArchitectureCost-efficient frontier unified reasoning modelHigh-Capacity Multilingual Transformer
ParametersConfidential32B
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPMUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($2/1M in) across full 1000K windowFlat rate ($0.25/1M in) across full 128K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0.1/1M (no extra cache-write fee)Cached input at $0.06/1M tokens
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative 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)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 20 GB VRAM (4-bit Quantized) · 69 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext
Output Modalitiestexttext

GPT-6 Sol vs Aya Expanse 32B: Respuestas Rápidas (FAQ)

Which is more intelligent, GPT-6 Sol or Aya Expanse 32B?

GPT-6 Sol is more intelligent. It scores 93 compared with 44 on the composite Intelligence Index.

Which model is faster?

GPT-6 Sol is faster, generating 116 tokens per second compared with 85 tokens per second.

Which model is cheaper to run?

Aya Expanse 32B is cheaper at $0.14 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Aya Expanse 32B has lower latency, with a time to first token of 0.44s compared with 1.16s.

Which model has a larger context window?

GPT-6 Sol has a larger context window, supporting 1M tokens compared with 128K tokens.

Veredicto

Choose GPT-6 Sol for costo-sensitive de frontera trabajo y codificación agéntica, or choose Aya Expanse 32B for global empresarial communications, international legal traducción, y académico investigación.

Preguntas frecuentes

Which is cheaper: GPT-6 Sol or Aya Expanse 32B?+

GPT-6 Sol costs $2/1M input and $10/1M output tokens, while Aya Expanse 32B costs $0.25/1M input and $0.5/1M output tokens.

Which model has a larger context window: GPT-6 Sol or Aya Expanse 32B?+

GPT-6 Sol supports 1M tokens whereas Aya Expanse 32B supports 128K tokens.

AI Terminology & Guide
Explore Glossary →

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

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: OpenAI & Cohere Official Documentation