Aya Expanse 32B vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Aya Expanse 32B by Cohere against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
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Aya Expanse 32B
Model Multibahasa GlobalAya Expanse 32B dari Cohere adalah model AI yang dirancang untuk penerjemahan multibahasa yang akurat dan komunikasi perusahaan global, menghadirkan jendela konteks 128K, kecepatan 85 token/detik, indeks kecerdasan 44/100, serta tarif $0.25
$0.25 / 1M
$0.50 / 1M
128K tokens
33.5%
GPT-6.1 Sol
Model Unggulan Garis DepanGPT-6.1 Sol dari OpenAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1M, kecepatan 120 token/detik, indeks kecerdasan 94/100, serta tarif $2
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Perbedaan Utama Sekilas
- Aya Expanse 32B is 13.3x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol has a larger context window (1M vs 128K tokens).
- GPT-6.1 Sol is faster at 120 tok/s vs 85 tok/s.
- GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 33.5%).
| Feature | Aya Expanse 32B | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 44 | 94 |
Provider | Cohere | OpenAI |
Input Price Cost per million input tokens | $0.25 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.50 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.14 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 8K | 128K |
Throughput Speed Tokens generated per second | 85 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | 33.5% | 82.3% |
GPQA Diamond Graduate-level reasoning | 50% | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.06 / 1M | $0.10 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Aya Expanse 32B · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 33.5% · GPQA Diamond 50%)
- Kecepatan generasi tinggi 85 token/detik dengan latensi token pertama (TTFT) hanya 440 ms
- Bobot terbuka (32B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
GPT-6.1 Sol · Strengths & Key Advantages
- Jendela konteks 1M dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 82.3% · GPQA Diamond 80.8%)
- Kecepatan generasi tinggi 120 token/detik dengan latensi token pertama (TTFT) hanya 1120 ms
- Skema harga API kompetitif (tarif $2/$10 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
- Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
- Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Aya Expanse 32B | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.18 | $2.05 |
Output Tokens / Task Tokens generated per task | 28K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Aya Expanse 32B | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | aya-expanse-32b | gpt-6-1-sol |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-10 | 2026-09 |
| Knowledge Cutoff | August 2024 | April 2026 |
| Architecture | High-Capacity Multilingual Transformer | Near-Astra unified reasoning model |
| Parameters | 32B | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.25/1M in) across full 128K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.06/1M tokens | Automatic prefix caching at $0.1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | BF16 / 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 Classification | Open-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 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
Aya Expanse 32B vs GPT-6.1 Sol: Jawaban Cepat (FAQ)
Which is more intelligent, Aya Expanse 32B or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 44 on the composite Intelligence Index.
Which model is faster?
GPT-6.1 Sol is faster, generating 120 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 1.12s.
Which model has a larger context window?
GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 128K tokens.
Kesimpulan
Choose Aya Expanse 32B for sangat cocok untuk penerjemahan multibahasa yang akurat dan komunikasi perusahaan global, sistem rag perusahaan, dan integrasi api skala produksi., or choose GPT-6.1 Sol for sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi ai, sistem rag perusahaan, dan integrasi api skala produksi..
Pertanyaan Umum (FAQ)
Which is cheaper: Aya Expanse 32B or GPT-6.1 Sol?+
Aya Expanse 32B costs $0.25/1M input and $0.5/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Aya Expanse 32B or GPT-6.1 Sol?+
Aya Expanse 32B supports 128K tokens whereas GPT-6.1 Sol supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Sumber resmi: Cohere & OpenAI Official Documentation