Mistral Medium 3 vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Mistral Medium 3 by Mistral AI against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
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Mistral Medium 3
Açık Ağırlıklı Temel ModelMistral AI tarafından geliştirilen Mistral Medium 3; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 131K bağlam penceresi, 85 token/sn hız, 47/100 zeka indeksi ve 1M token başın
$0.40 / 1M
$2.00 / 1M
131.1K tokens
40.5%
GPT-6.1 Sol
Amiral Gemisi Öncü ModelOpenAI tarafından geliştirilen GPT-6.1 Sol; öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli AI iş akışları için tasarlanmış olup 1M bağlam penceresi, 120 token/sn hız, 94/100 zeka indeksi ve 1M token başına $2/$10 fiyatland
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Bir Bakışta Temel Farklar
- Mistral Medium 3 is 4.8x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol has a larger context window (1M vs 131K 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 40.5%).
| Feature | Mistral Medium 3 | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 47 | 94 |
Provider | Mistral AI | OpenAI |
Input Price Cost per million input tokens | $0.40 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.35 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 85 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | 40.5% | 82.3% |
GPQA Diamond Graduate-level reasoning | 57.5% | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $0.10 / 1M |
Hangi Alanda Kim Kazanıyor?
At-a-glance decision frameworkDoğrulanmış Benchmark Puanları
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.
Gecikme Süresi ve Yanıt Hızı
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Gerçek Zamanlı Token Maliyet Simülatörü
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Mistral Medium 3 · Strengths & Key Advantages
- 131K bağlam penceresi ve yanıt başına maksimum 16K çıktı tokenı kapasitesi (SWE-bench Verified 40.5% · GPQA Diamond 57.5%)
- Sadece 480 ms ilk token gecikmesi (TTFT) ile saniyede 85 token yüksek üretim hızı
- vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (Confidential (~70B))
Considerations & Trade-offs
- Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
- Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir
GPT-6.1 Sol · Strengths & Key Advantages
- 1M bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 82.3% · GPQA Diamond 80.8%)
- Sadece 1120 ms ilk token gecikmesi (TTFT) ile saniyede 120 token yüksek üretim hızı
- İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2/$10 fiyatlandırma)
Considerations & Trade-offs
- Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
- Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Mistral Medium 3 | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.35 | $2.05 |
Output Tokens / Task Tokens generated per task | 35K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | Mistral Medium 3 | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | mistral-medium-3-latest | gpt-6-1-sol |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-05 | 2026-09 |
| Knowledge Cutoff | March 2025 | April 2026 |
| Architecture | Enterprise Multimodal Transformer | Near-Astra unified reasoning model |
| Parameters | Confidential (~70B) | 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 ($0.4/1M in) across full 131K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.1/1M 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) · Vision (~258–765 tokens per image tile) | 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) · 43 GB VRAM (4-bit Quantized) · 151 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, vision | text, vision |
| Output Modalities | text | text |
Mistral Medium 3 vs GPT-6.1 Sol: Hızlı Yanıtlar (SSS)
Which is more intelligent, Mistral Medium 3 or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 47 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?
Mistral Medium 3 is cheaper at $0.35 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Mistral Medium 3 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 131.1K tokens.
Sonuç
Choose Mistral Medium 3 for özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir., or choose GPT-6.1 Sol for öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli ai iş akışları, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir..
Sıkça Sorulan Sorular (SSS)
Which is cheaper: Mistral Medium 3 or GPT-6.1 Sol?+
Mistral Medium 3 costs $0.4/1M input and $2/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Mistral Medium 3 or GPT-6.1 Sol?+
Mistral Medium 3 supports 131K 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.
Resmi kaynaklar: Mistral AI & OpenAI Official Documentation