Head-to-Head Model Comparison

Aya Vision 32B vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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Compare Aya Vision 32B by Cohere against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

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Cohere

Aya Vision 32B

Multilingual VLM

High-capacity 32B multilingual vision model delivering deep visual reasoning, diagram analysis, and rich document understanding across 23 languages.

Intelligence Index45 / 100
Input Token:

$0.35 / 1M

Output Token:

$0.80 / 1M

Context Window:

16K tokens

SWE-bench Verified:

32%

OpenAI

GPT-6.1 Sol

Near-Astra Value

Delivers results close to GPT-6 Astra at roughly one fifth of the price — the latest 2026 release.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Key Differences at a Glance

  • Aya Vision 32B is 8.9x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol has a larger context window (1M vs 16K tokens).
  • GPT-6.1 Sol is faster at 120 tok/s vs 75 tok/s.
  • GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 32.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureAya Vision 32BGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
4594
Provider
CohereOpenAI
Input Price
Cost per million input tokens
$0.35 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.80 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.21 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
16K tokens~24 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K128K
Throughput Speed
Tokens generated per second
75 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
32%82.3%
GPQA Diamond
Graduate-level reasoning
51.5%80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.08 / 1M$0.10 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
GPT-6.1 Sol
+50.3% SWE-bench lead
Cost
Aya Vision 32B
8.9x cheaper monthly runtime
Speed
GPT-6.1 Sol
+60% faster generation
Context
GPT-6.1 Sol
1M tokens window

Empirical Head-to-Head Benchmark Scores

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

Aya Vision 32BGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

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

32%vs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

51.5%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

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

74%vs89.9%
LMSYS Chatbot Arena Elo

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

1280ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs63.6%
SciCode (Scientific Computing)

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

N/Avs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.7%
AIME (Advanced Math Competition)

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

N/Avs93.5%
Long-Context Reasoning

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

N/Avs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs120 tok/s

Latency & Response Time

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
Aya Vision 32B0.48s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Aya Vision 32B7.15s
GPT-6.1 Sol5.29s

Real-Time Interactive Token Cost Simulator

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)
Aya Vision 32B Monthly API Bill
$1.36 / month
$0.35/1M in · $0.8/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Aya Vision 32B saves approximately $10.79 / month (89%) under this workload.8.9x Savings

Aya Vision 32B · Strengths & Key Advantages

  • Deep multilingual diagram, chart, and technical drawing comprehension
  • Significantly higher accuracy on complex visual question answering across 23 languages
  • Open weights available for private corporate hosting
Considerations & Trade-offs
  • 16K context limit requires chunking for massive multi-page documents
  • Video streams not supported

GPT-6.1 Sol · Strengths & Key Advantages

  • Near-Astra results at roughly a fifth of the cost
  • Excellent coding and long-horizon agent performance
  • Strong reliability with far lower latency than Astra
  • Near-flagship results at roughly a fifth of the price
Considerations & Trade-offs
  • Still marginally behind Astra on the very hardest reasoning
  • Same price as GPT-6 Sol, so the upgrade decision is easy

Token Use & Task Economics

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

MetricAya Vision 32BGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.22$2.05
Output Tokens / Task
Tokens generated per task
25K62K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureAya Vision 32BGPT-6.1 Sol
Official API Model ID (SDK)aya-vision-32bgpt-6-1-sol
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2025-032026-09
Knowledge CutoffJanuary 2025April 2026
ArchitectureHigh-Capacity Multilingual VLMNear-Astra unified reasoning model
Parameters32BConfidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.35/1M in) across full 16K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.08/1M tokensAutomatic prefix caching at $0.1/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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 & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText 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 VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 20 GB VRAM (4-bit Quantized) · 69 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)OpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Aya Vision 32B vs GPT-6.1 Sol: Quick Answers

Which is more intelligent, Aya Vision 32B or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 45 on the composite Intelligence Index.

Which model is faster?

GPT-6.1 Sol is faster, generating 120 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

Aya Vision 32B is cheaper at $0.21 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Aya Vision 32B has lower latency, with a time to first token of 0.48s 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 16K tokens.

Verdict

Choose Aya Vision 32B for international patent document inspection, global medical chart ocr, and multilingual enterprise analytics, or choose GPT-6.1 Sol for the best value frontier model for professional and agentic work.

Frequently asked questions

Which is cheaper: Aya Vision 32B or GPT-6.1 Sol?+

Aya Vision 32B costs $0.35/1M input and $0.8/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Aya Vision 32B or GPT-6.1 Sol?+

Aya Vision 32B supports 16K tokens whereas GPT-6.1 Sol supports 1M 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.

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.

Sources: Cohere & OpenAI Official Documentation