GPT-5.1 Codex Max vs Devstral 2
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-5.1 Codex Max dari OpenAI dan Devstral 2 dari Mistral AI adalah dua model AI unggulan. GPT-5.1 Codex Max menawarkan jendela konteks 400K token dengan harga $1.75/$14.00 per 1 juta token, sedangkan Devstral 2 menyediakan konteks 262.1K token seharga $1.50/$4.50 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
Ganti & Bandingkan Model Apa Saja
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
GPT-5.1 Codex Max
Model Unggulan Garis DepanGPT-5.1 Codex Max dari OpenAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 400K, kecepatan 95 token/detik, indeks kecerdasan 62/100, serta t
$1.75 / 1M
$14.00 / 1M
400K tokens
78.2%
Devstral 2
Model Agen Otonom & AlatDevstral 2 dari Mistral AI adalah model AI yang dirancang untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, menghadirkan jendela konteks 262K, kecepatan 70 token/detik, indeks kecerdasan 56/100, s
$1.50 / 1M
$4.50 / 1M
262.1K tokens
58.2%
Perbedaan Utama Sekilas
- Devstral 2 is 2.3x cheaper for API usage (input + output tokens combined).
- GPT-5.1 Codex Max has a larger context window (400K vs 262K tokens).
- GPT-5.1 Codex Max is faster at 95 tok/s vs 70 tok/s.
- GPT-5.1 Codex Max leads on SWE-bench coding (78.2% vs 58.2%).
| Feature | GPT-5.1 Codex Max | Devstral 2 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 62 | 56 |
Provider | OpenAI | Mistral AI |
Input Price Cost per million input tokens | $1.75 / 1M | $1.50 / 1M |
Output Price Cost per million output tokens | $14.00 / 1M | $4.50 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.87 / 1M | $0.99 / 1M |
Context Window Maximum input + output tokens | 400K tokens~600 A4 pages of text | 262.1K tokens~393 A4 pages of text |
Max Output Tokens Per single request | 128K | 66K |
Throughput Speed Tokens generated per second | 95 tok/s | 70 tok/s |
SWE-bench Verified Real-world software engineering | 78.2% | 58.2% |
GPQA Diamond Graduate-level reasoning | 80% | 66.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.17 / 1M | $0.35 / 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.
GPT-5.1 Codex Max · Strengths & Key Advantages
- Jendela konteks 400K dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 78.2% · GPQA Diamond 80%)
- Kecepatan generasi tinggi 95 token/detik dengan latensi token pertama (TTFT) hanya 1700 ms
- Skema harga API kompetitif (tarif $1.75/$14 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
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Devstral 2 · Strengths & Key Advantages
- Jendela konteks 262K dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 58.2% · GPQA Diamond 66.5%)
- Kecepatan generasi tinggi 70 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
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-5.1 Codex Max | Devstral 2 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.40 | $0.65 |
Output Tokens / Task Tokens generated per task | 62K | 42K |
Reasoning Tokens / Task Thinking tokens burned per task | 36K | 20K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-5.1 Codex Max | Devstral 2 |
|---|---|---|
| Official API Model ID (SDK) | gpt-5-1-codex-max | devstral-2-latest |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-11 | 2025-12 |
| Knowledge Cutoff | October 2024 | October 2025 |
| Architecture | Maximum-capability code-specialised reasoning model | Advanced Agentic Code Transformer |
| Parameters | Confidential | 123B |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($1.75/1M in) across full 400K window | Flat rate ($1.5/1M in) across full 262K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.175/1M (no extra cache-write fee) | Cached input at $0.35/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 76 GB VRAM (4-bit Quantized) · 264 GB VRAM (Native BF16) |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text, vision | text |
| Output Modalities | text | text |
GPT-5.1 Codex Max vs Devstral 2: Jawaban Cepat (FAQ)
Which is more intelligent, GPT-5.1 Codex Max or Devstral 2?
GPT-5.1 Codex Max is more intelligent. It scores 62 compared with 56 on the composite Intelligence Index.
Which model is faster?
GPT-5.1 Codex Max is faster, generating 95 tokens per second compared with 70 tokens per second.
Which model is cheaper to run?
Devstral 2 is cheaper at $0.99 per 1M tokens blended, compared with $1.87 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Devstral 2 has lower latency, with a time to first token of 0.52s compared with 1.70s.
Which model has a larger context window?
GPT-5.1 Codex Max has a larger context window, supporting 400K tokens compared with 262.1K tokens.
Kesimpulan
Baik GPT-5.1 Codex Max (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Devstral 2 (Sangat cocok untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: GPT-5.1 Codex Max unggul dalam penalaran dan pemrograman, GPT-5.1 Codex Max memberikan kecepatan generasi token lebih tinggi, dan Devstral 2 lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, GPT-5.1 Codex Max atau Devstral 2?+
Dalam indeks kecerdasan gabungan dan benchmark coding, GPT-5.1 Codex Max memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API GPT-5.1 Codex Max vs Devstral 2?+
GPT-5.1 Codex Max mengenakan biaya $1.75 / $14.00 per 1M token input/output, sedangkan Devstral 2 sebesar $1.50 / $4.50. Secara keseluruhan, Devstral 2 lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
GPT-5.1 Codex Max mendukung konteks 400K token dibandingkan 262.1K token pada Devstral 2, sementara GPT-5.1 Codex Max 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
- Devstral 2 vs Claude Sonnet 5.5: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Devstral 2 vs Qwen3-Coder 480B-A35B Instruct: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-5.1 Codex Max vs Claude Opus 5.5: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-5.1 Codex Max vs Claude Sonnet 5.5: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-5.1 Codex vs Devstral 2: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-5.2 Codex vs Devstral 2: 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 OpenAI & Mistral AI serta evaluasi benchmark independen (2026).