Head-to-Head Model Comparison

Aya Vision 32B vs Aya Vision 8B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Aya Vision 32B vs Aya Vision 8B: Benchmarks, Pricing & Speed Comparison

Aya Vision 32B by Cohere and Aya Vision 8B by Cohere represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Aya Vision 8B holds a notable pricing advantage for token ingestion. On output generation, Aya Vision 8B is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 16K tokens. In latency-sensitive production environments, Aya Vision 8B leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

Perbandingan Langsung (VS)

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Cohere

Aya Vision 32B

Model Open-Weights

Aya Vision 32B dari Cohere adalah model AI canggih dengan jendela konteks 16K token serta harga API $0.35/1M token input dan $0.8/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

Intelligence Index45 / 100
Input Token:

$0.35 / 1M

Output Token:

$0.80 / 1M

Context Window:

16K tokens

SWE-bench Verified:

32%

Cohere

Aya Vision 8B

Model Open-Weights

Aya Vision 8B dari Cohere adalah model AI canggih dengan jendela konteks 16K token serta harga API $0.1/1M token input dan $0.25/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

Intelligence Index38 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.25 / 1M

Context Window:

16K tokens

SWE-bench Verified:

22%

Perbedaan Utama Sekilas

  • Aya Vision 8B is 3.2x cheaper for API usage (input + output tokens combined).
  • Aya Vision 8B is faster at 110 tok/s vs 75 tok/s.
  • Aya Vision 32B leads on SWE-bench coding (32.0% vs 22.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureAya Vision 32BAya Vision 8B
Intelligence Index
Composite reasoning & knowledge score (0-100)
4538
Provider
CohereCohere
Input Price
Cost per million input tokens
$0.35 / 1M$0.10 / 1M
Output Price
Cost per million output tokens
$0.80 / 1M$0.25 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.21 / 1M$0.07 / 1M
Context Window
Maximum input + output tokens
16K tokens~24 A4 pages of text16K tokens~24 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
75 tok/s110 tok/s
SWE-bench Verified
Real-world software engineering
32%22%
GPQA Diamond
Graduate-level reasoning
51.5%41%
Cached Input Price
Prompt caching discount per 1M tokens
$0.08 / 1M$0.03 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding
Aya Vision 32B
+10.0% SWE-bench lead
Cost
Aya Vision 8B
3.2x cheaper monthly runtime
Speed
Aya Vision 8B
+47% faster generation
Context
Tied
16K tokens window

Skor Benchmark Terverifikasi

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

Aya Vision 32BAya Vision 8B
SWE-bench Verified (Autonomous Coding)

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

32%vs22%
GPQA Diamond (Doctorate-Level Science & Math)

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

51.5%vs41%
MMLU-Pro (Multi-task Language Understanding)

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

74%vs64%
LMSYS Chatbot Arena Elo

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

1280ptsvs1220pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs110 tok/s

Latensi & Waktu Respons

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
Aya Vision 8B0.35s
Est. End-to-End Response (500 tokens)TTFT + generation time
Aya Vision 32B7.15s
Aya Vision 8B4.90s

Simulator Biaya Token Interaktif

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
Aya Vision 8B Monthly API Bill
$0.42 / month
$0.1/1M in · $0.25/1M out
Aya Vision 8B saves approximately $0.94 / month (69%) under this workload.3.2x Savings

Aya Vision 32B · Strengths & Key Advantages

  • Arsitektur High-Capacity Multilingual VLM mutakhir dari Cohere dengan dukungan konteks 16K token
  • Efisiensi biaya API yang kompetitif ($0.35/1M input, $0.8/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

Aya Vision 8B · Strengths & Key Advantages

  • Arsitektur Multilingual Vision-Language Transformer mutakhir dari Cohere dengan dukungan konteks 16K token
  • Efisiensi biaya API yang kompetitif ($0.1/1M input, $0.25/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

Token Use & Task Economics

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

MetricAya Vision 32BAya Vision 8B
Cost per Task
Estimated USD to finish one task
$0.22$0.06
Output Tokens / Task
Tokens generated per task
25K18K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureAya Vision 32BAya Vision 8B
Official API Model ID (SDK)aya-vision-32baya-vision-8b
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-032025-03
Knowledge CutoffJanuary 2025January 2025
ArchitectureHigh-Capacity Multilingual VLMMultilingual Vision-Language Transformer
Parameters32B8B
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($0.35/1M in) across full 16K windowFlat rate ($0.1/1M in) across full 16K window
Prompt Cache Policy & TTLCached input at $0.08/1M tokensCached input at $0.03/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)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 & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)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) · 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)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 ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Aya Vision 32B vs Aya Vision 8B: Jawaban Cepat (FAQ)

Which is more intelligent, Aya Vision 32B or Aya Vision 8B?

Aya Vision 32B is more intelligent. It scores 45 compared with 38 on the composite Intelligence Index.

Which model is faster?

Aya Vision 8B is faster, generating 110 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

Aya Vision 8B is cheaper at $0.07 per 1M tokens blended, compared with $0.21 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Aya Vision 8B has lower latency, with a time to first token of 0.35s compared with 0.48s.

Kesimpulan

Verdict & Model Selection Recommendation: Choose Aya Vision 32B if your priority is International patent document inspection, global medical chart OCR, and multilingual enterprise analytics. Its performance in demanding tasks justifies its operational token cost. Choose Aya Vision 8B if your workflow prioritizes Global document triage, multilingual receipt and invoice OCR, and mobile visual apps. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Pertanyaan Umum (FAQ)

How does Aya Vision 32B compare to Aya Vision 8B in API token pricing and cost per token?+

Aya Vision 32B costs $0.35 per 1M input tokens and $0.80 per 1M output tokens, whereas Aya Vision 8B costs $0.10 input and $0.25 output. Overall, Aya Vision 8B is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Aya Vision 32B or Aya Vision 8B?+

Both Aya Vision 32B and Aya Vision 8B offer an identical context window of 16K tokens (~12k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.

Which AI model is better for software engineering and coding: Aya Vision 32B or Aya Vision 8B?+

Aya Vision 32B scores 32% on SWE-bench Verified while Aya Vision 8B scores 22%. For autonomous software engineering and multi-file debugging, Aya Vision 32B holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Aya Vision 32B and Aya Vision 8B?+

Aya Vision 32B is optimized for low-latency direct generation. In contrast, Aya Vision 8B focuses on standard fast inference.

How does inference speed (tokens per second) compare between Aya Vision 32B and Aya Vision 8B?+

Aya Vision 32B generates approximately 75 tokens per second, while Aya Vision 8B delivers 110 tokens per second. In latency-sensitive production environments, Aya Vision 8B provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Aya Vision 32B and Aya Vision 8B to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Aya Vision 8B to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Aya Vision 32B. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
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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.

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