Mistral Large 2 vs GPT-4o
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Mistral Large 2 dari Mistral AI dan GPT-4o dari OpenAI adalah dua model AI unggulan. Mistral Large 2 menawarkan jendela konteks 128K token dengan harga $2.00/$6.00 per 1 juta token, sedangkan GPT-4o menyediakan konteks 128K token seharga $2.50/$10.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Mistral Large 2
Model Dasar Bobot TerbukaMistral Large 2 dari Mistral AI adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 128K, kecepatan 75 token/detik, indeks kecerdasan 46/100, serta tarif
$2.00 / 1M
$6.00 / 1M
128K tokens
38%
GPT-4o
Model Suara & Audio AsliGPT-4o dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 128K, kecepatan 105 token/detik, indeks kecerdasan 41/100, serta tarif $2.5/$10 p
$2.50 / 1M
$10.00 / 1M
128K tokens
38.8%
Perbedaan Utama Sekilas
- Mistral Large 2 is 1.5x cheaper for API usage (input + output tokens combined).
- GPT-4o is faster at 105 tok/s vs 75 tok/s.
- GPT-4o leads on SWE-bench coding (38.8% vs 38.0%).
| Feature | Mistral Large 2 | GPT-4o |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 46 | 41 |
Provider | Mistral AI | OpenAI |
Input Price Cost per million input tokens | $2.00 / 1M | $2.50 / 1M |
Output Price Cost per million output tokens | $6.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.70 / 1M | $2.38 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 8K | 16K |
Throughput Speed Tokens generated per second | 75 tok/s | 105 tok/s |
SWE-bench Verified Real-world software engineering | 38% | 38.8% |
GPQA Diamond Graduate-level reasoning | 54% | 53.6% |
Cached Input Price Prompt caching discount per 1M tokens | $1.00 / 1M | $1.25 / 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.
Mistral Large 2 · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 38% · GPQA Diamond 54%)
- Kecepatan generasi tinggi 75 token/detik dengan latensi token pertama (TTFT) hanya 520 ms
- Bobot terbuka (123B) 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
- Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya
GPT-4o · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
- Kecepatan generasi tinggi 105 token/detik dengan latensi token pertama (TTFT) hanya 410 ms
- Skema harga API kompetitif (tarif $2.5/$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 | Mistral Large 2 | GPT-4o |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $0.68 |
Output Tokens / Task Tokens generated per task | 24K | 24K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Mistral Large 2 | GPT-4o |
|---|---|---|
| Official API Model ID (SDK) | mistral-large-2-latest | gpt-4o |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-07 | 2024-05 |
| Knowledge Cutoff | July 2024 | October 2023 |
| Architecture | 123B Dense Frontier Transformer | Omni-Multimodal Dense |
| Parameters | 123B | 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) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($2/1M in) across full 128K window | Flat rate ($2.5/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Cached input at $1/1M tokens | Automatic prefix caching at $1.25/1M (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) · Audio (~25–32 tokens/sec) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 76 GB VRAM (4-bit Quantized) · 264 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, audio |
| Output Modalities | text | text, audio |
Mistral Large 2 vs GPT-4o: Jawaban Cepat (FAQ)
Which is more intelligent, Mistral Large 2 or GPT-4o?
Mistral Large 2 is more intelligent. It scores 46 compared with 41 on the composite Intelligence Index.
Which model is faster?
GPT-4o is faster, generating 105 tokens per second compared with 75 tokens per second.
Which model is cheaper to run?
Mistral Large 2 is cheaper at $1.70 per 1M tokens blended, compared with $2.38 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-4o has lower latency, with a time to first token of 0.41s compared with 0.52s.
Kesimpulan
Baik Mistral Large 2 (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-4o (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Mistral Large 2 unggul dalam penalaran dan pemrograman, GPT-4o memberikan kecepatan generasi token lebih tinggi, dan Mistral Large 2 lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Mistral Large 2 atau GPT-4o?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Mistral Large 2 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Mistral Large 2 vs GPT-4o?+
Mistral Large 2 mengenakan biaya $2.00 / $6.00 per 1M token input/output, sedangkan GPT-4o sebesar $2.50 / $10.00. Secara keseluruhan, Mistral Large 2 lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Mistral Large 2 mendukung konteks 128K token dibandingkan 128K token pada GPT-4o, sementara GPT-4o unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Claude 3.5 Sonnet vs GPT-4o: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
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- GPT-4o vs Gemini 1.5 Pro: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-4o vs GPT-4 Turbo: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Grok 2 vs GPT-4o: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
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: Dokumentasi API resmi Mistral AI & OpenAI serta evaluasi benchmark independen (2026).