Head-to-Head Model Comparison

GPT-6.1 Sol vs Aya Expanse 8B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
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Compare GPT-6.1 Sol by OpenAI against Aya Expanse 8B by Cohere across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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GPT-6.1 Sol

Valeur proche d'Astra

offre results close à GPT-6 Astra à roughly one fifth du prix — le latest 2026 version.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Cohere

Aya Expanse 8B

Multilingue

compact ouvert multilingue modèle méticuleusement trained à travers 23 langues, bridging langue divides dans faible-resource linguistic environments.

Intelligence Index36 / 100
Input Token:

$0.08 / 1M

Output Token:

$0.16 / 1M

Context Window:

8.2K tokens

SWE-bench Verified:

24%

Différences Clés en un Coup d’Œil

  • Aya Expanse 8B is 41.3x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol has a larger context window (1M vs 8K tokens).
  • Aya Expanse 8B is faster at 135 tok/s vs 120 tok/s.
  • GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 24.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueGPT-6.1 SolAya Expanse 8B
Intelligence Index
Composite reasoning & knowledge score (0-100)
9436
Provider
OpenAICohere
Input Price
Cost per million input tokens
$2.00 / 1M$0.08 / 1M
Output Price
Cost per million output tokens
$10.00 / 1M$0.16 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.47 / 1M$0.05 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text8.2K tokens~12 A4 pages of text
Max Output Tokens
Per single request
128K4K
Throughput Speed
Tokens generated per second
120 tok/s135 tok/s
SWE-bench Verified
Real-world software engineering
82.3%24%
GPQA Diamond
Graduate-level reasoning
80.8%40%
Cached Input Price
Prompt caching discount per 1M tokens
$0.10 / 1M$0.02 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
GPT-6.1 Sol
+58.3% SWE-bench lead
Coût
Aya Expanse 8B
41.3x cheaper monthly runtime
Vitesse
Aya Expanse 8B
+13% faster generation
Contexte
GPT-6.1 Sol
1M tokens window

Scores de Benchmarks Vérifiés

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

GPT-6.1 SolAya Expanse 8B
SWE-bench Verified (Autonomous Coding)

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

82.3%vs24%
GPQA Diamond (Doctorate-Level Science & Math)

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

80.8%vs40%
MMLU-Pro (Multi-task Language Understanding)

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

89.9%vs62%
LMSYS Chatbot Arena Elo

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

1519ptsvs1205pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

18.1%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

63.6%vsN/A
SciCode (Scientific Computing)

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

54.8%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

79.7%vsN/A
AIME (Advanced Math Competition)

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

93.5%vsN/A
Long-Context Reasoning

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

91%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs135 tok/s

Latence et Temps de Réponse

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-6.1 Sol1.12s
Aya Expanse 8B0.30s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-6.1 Sol5.29s
Aya Expanse 8B4.00s

Simulateur Interactif de Coût 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-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Aya Expanse 8B Monthly API Bill
$0.29 / month
$0.08/1M in · $0.16/1M out
Aya Expanse 8B saves approximately $11.86 / month (98%) under this workload.41.3x Savings

GPT-6.1 Sol · Strengths & Key Advantages

  • Near-Astra results à roughly un fifth du coût
  • Excellent codage et à long terme agent performances
  • solide reliability avec far inférieur latence que Astra
  • Near-phare results à roughly un fifth du prix
Considerations & Trade-offs
  • Still marginally behind Astra sur le très hardest raisonnement
  • Same prix as GPT-6 Sol, so le upgrade decision est easy

Aya Expanse 8B · Strengths & Key Advantages

  • spécialement conçu dataset covering 23 diverse langues avec supérieur cultural contexte
  • léger 8B empreinte running smoothly sur grand public et laptop GPUs
  • solide multilingue traduction et cross-lingual texte résumé
Considerations & Trade-offs
  • fenêtre de contexte limité à 8K tokens
  • inférieur capacité sur advanced codage et competition mathematics

Token Use & Task Economics

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

MetricGPT-6.1 SolAya Expanse 8B
Cost per Task
Estimated USD to finish one task
$2.05$0.04
Output Tokens / Task
Tokens generated per task
62K18K
Reasoning Tokens / Task
Thinking tokens burned per task
36K0K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueGPT-6.1 SolAya Expanse 8B
Official API Model ID (SDK)gpt-6-1-solaya-expanse-8b
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-092024-10
Knowledge CutoffApril 2026August 2024
ArchitectureNear-Astra unified reasoning modelCompact Multilingual Dense Transformer
ParametersConfidential8B
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 ($0.08/1M in) across full 8K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0.1/1M (no extra cache-write fee)Cached input at $0.02/1M 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) · 5 GB VRAM (4-bit Quantized) · 17 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-6.1 Sol vs Aya Expanse 8B: Réponses Rapides (FAQ)

Which is more intelligent, GPT-6.1 Sol or Aya Expanse 8B?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 36 on the composite Intelligence Index.

Which model is faster?

Aya Expanse 8B is faster, generating 135 tokens per second compared with 120 tokens per second.

Which model is cheaper to run?

Aya Expanse 8B is cheaper at $0.05 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Aya Expanse 8B has lower latency, with a time to first token of 0.30s compared with 1.12s.

Which model has a larger context window?

GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 8.2K tokens.

Verdict

Choose GPT-6.1 Sol for le meilleur valeur modèle de pointe pour professionnel et agentic travail, or choose Aya Expanse 8B for multilingue client interaction, faible-resource langue traduction, et périphérie déploiements.

Questions fréquentes

Which is cheaper: GPT-6.1 Sol or Aya Expanse 8B?+

GPT-6.1 Sol costs $2/1M input and $10/1M output tokens, while Aya Expanse 8B costs $0.08/1M input and $0.16/1M output tokens.

Which model has a larger context window: GPT-6.1 Sol or Aya Expanse 8B?+

GPT-6.1 Sol supports 1M tokens whereas Aya Expanse 8B supports 8K 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.

Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: OpenAI & Cohere Official Documentation