The week across the frontier labs — new defaults, previews and open-weight releases — plus where the coding benchmarks stand.
Frontier models — (23 Oct) OpenAI announced it will no longer train its frontier AI models on the live internet, citing significant risks. The shift comes shortly after an engineer suggested the approach was unworkable. · 23 Oct
Read → TechCrunchChatGPT infrastructure — (23 Oct) OpenAI detailed how it scaled its Habitat storage system to serve over one billion ChatGPT users. The update highlights reliable multi-tenancy and global caching to deliver significantly faster read speeds. · 23 Oct
Read → OpenAIFrontier model training — (23 Oct) OpenAI outlined enhancements to its frontier model training and evaluation environment to strengthen containment. The measures include isolated offline environments and high-compute red-teaming protocols. · 23 Oct
Read → OpenAIAI safety — (23 Oct) OpenAI is partnering with Poland’s NASK to advance AI safety, security, and technical research. The collaboration aims to strengthen digital safeguards and support a more resilient ecosystem. · 23 Oct
Read → OpenAIThe full AI Models Comparison dashboard — every category, factor weights, best-for and sources. Benchmark-anchored; ✅ verified · ⚠️ partial · ❓ released, not yet independently benchmarked. Wide tables scroll sideways.
| # | Model | Score | Business use | Web research | Presentation | Low halluc. | Coding | Tool use | Docs | Cost (in/out $) | Open? | Conf. |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Claude Fable 5 | 93 | ● 95 | ● 90 | ● 93 | ● 96 | ● 97 | ● 95 | ● 94 | $10 / $50 | No | ✅ |
| 2 | Claude Opus 4.8 | 90 | ● 93 | ● 82 | ● 91 | ● 92 | ● 93 | ● 92 | ● 93 | $5 / $25 | No | ✅ |
| 3 | GPT-5.6 Sol | 89 | ● 90 | ● 90 | ● 88 | ● 82 | ● 92 | ● 92 | ● 90 | $5 / $30 | No | ✅ |
| 4 | Claude Sonnet 5 | 86 | ● 90 | ● 80 | ● 88 | ● 89 | ● 89 | ● 90 | ● 90 | $3 / $15* | No | ✅ |
| 5 | Kimi K2.6 | 86 | ● 88 | ● 92 | ● 88 | ● 95 | ● 90 | ● 94 | ● 88 | $0.95 / $4.00 | Yes | ✅ |
| 6 | GLM-5.2 | 83 | ● 78 | ● 78 | ● 76 | ● 80 | ● 88 | ● 86 | ● 76 | $1.40 / $4.40 | Yes | ✅ |
| 7 | Qwen 3.7-Max | 83 | ● 80 | ● 74 | ● 78 | ● 78 | ● 86 | ● 88 | ● 76 | $1.25 / $3.75* | No | ✅ |
| 8 | GPT-5.6 Terra | 82 | ● 84 | ● 84 | ● 80 | ● 80 | ● 86 | ● 85 | ● 84 | $2.50 / $15.00 | No | ✅ |
| 9 | Grok 4.5 | 82 | ● 78 | ● 82 | ● 76 | ● 78 | ● 86 | ● 84 | ● 76 | $2 / $6 | No | ✅ |
| 10 | Kimi K2.7-Code | 82 | ● 78 | ● 80 | ● 76 | ● 90 | ● 93 | ● 90 | ● 78 | $0.95 / $4.00 | Yes | ⚠️ |
| 11 | GLM-5V-Turbo (vision) | 81 | ● 78 | ● 76 | ● 82 | ● 76 | ● 90 | ● 86 | ● 82 | $1.20 / $4.00 | No | ⚠️ |
| 12 | Gemini 3.5 Flash | 81 | ● 76 | ● 88 | ● 78 | ● 80 | ● 85 | ● 82 | ● 76 | $1.50 / $9.00 | No | ✅ |
| 13 | DeepSeek V4-Pro | 81 | ● 78 | ● 75 | ● 76 | ● 82 | ● 86 | ● 80 | ● 78 | $0.44 / $0.87 | Yes | ⚠️ |
| 14 | MiniMax M3 | 78 | ● 75 | ● 88 | ● 76 | ● 75 | ● 82 | ● 80 | ● 78 | $0.30 / $1.20 | Yes | ⚠️ |
| 15 | DeepSeek V4-Flash | 75 | ● 70 | ● 68 | ● 68 | ● 74 | ● 82 | ● 74 | ● 70 | $0.14 / $0.28 | Yes | ✅ |
| 16 | MiMo-V2.5-Pro | 73 | ● 72 | ● 70 | ● 72 | ● 74 | ● 80 | ● 76 | ● 74 | $0.44 / $0.87 | No | ✅ |
| 17 | GPT-5.6 Luna | 72 | ● 72 | ● 74 | ● 70 | ● 76 | ● 74 | ● 74 | ● 72 | $1 / $6 | No | ✅ |
| 18 | ERNIE 5.1 | 72 | ● 74 | ● 72 | ● 72 | ● 74 | ● 74 | ● 72 | ● 74 | $0.59 / $2.65 | No | ✅ |
| 19 | Qwen 3.7-Plus | 72 | ● 74 | ● 72 | ● 74 | ● 76 | ● 82 | ● 76 | ● 74 | $0.32 / $1.28 | No | ⚠️ |
| # | Model | Score | Egyptian quality | Naturalness | Emotion | Cloning | Real-time | $/min audio | Conf. |
|---|---|---|---|---|---|---|---|---|---|
| 1 | gpt-realtime-1.5 | 90 | ● 95 | ● 92 | ● 85 | ● 70 | ● 85 | ~$0.18–0.46/min | ⚠️ |
| 2 | Grok Voice Agent | 88 | ● 95 | ● 90 | ● 85 | ● 88 | ● 95 | $0.05/min · 2-min clone | ✅ |
| 3 | gpt-realtime-mini | 80 | ● 92 | ● 85 | ● 85 | ● 60 | ● 90 | $0.063–0.146/min | ❓ |
| 4 | Gemini 3.1 Flash Live | 78 | ● 82 | ● 86 | ● 78 | ● 0 | ● 92 | ~$0.008/min | ⚠️ |
| 5 | GLM-4-Voice | 55 | ● 30 | ● 80 | ● 75 | ● 60 | ● 90 | Open · CN/EN only | ⚠️ |
| # | Model | Score | Egyptian quality | Naturalness | Emotion | Cloning | Latency | $/min audio | Conf. |
|---|---|---|---|---|---|---|---|---|---|
| 1 | ElevenLabs v3 Multilingual | 88 | ● 92 | ● 95 | ● 95 | ● 95 | ● 80 | $0.10–0.30/1K chars · Egyptian ✅ | ✅ |
| 2 | Grok TTS | 86 | ● 90 | ● 88 | ● 80 | ● 85 | ● 92 | $4.20/1M chars · 120s clone | ✅ |
| 3 | ElevenLabs Flash / Turbo | 78 | ● 85 | ● 88 | ● 80 | ● 90 | ● 95 | $0.05/1K chars · ~75ms | ✅ |
| 4 | Microsoft MAI-Voice-2 | 70 | ● 60 | ● 85 | ● 78 | ● 0 | ● 80 | $22/1M chars · Arabic ⚠️ | ⚠️ |
| 5 | GLM-TTS | 68 | ● 55 | ● 85 | ● 80 | ● 88 | ● 85 | Open · 3s clone | ⚠️ |
| 6 | Mistral Voxtral TTS | 66 | ● 55 | ● 82 | ● 72 | ● 0 | ● 80 | $0.016/1K chars | ⚠️ |
| # | Model | Score | Egyptian / Arabic | Languages | Real-time | Accuracy | $/min audio | Conf. |
|---|---|---|---|---|---|---|---|---|
| 1 | Grok STT | 82 | ● 85 | 25 | ● 90 | ● 92 | $0.10/hr batch · diarization | ✅ |
| 2 | GLM-ASR-2512 | 76 | ● 80 | 30 | ● 90 | ● 88 | Open · Arabic ✅ | ⚠️ |
| 3 | ElevenLabs Scribe v2 | 76 | ● 78 | 90 | ● 90 | ● 91 | $0.39/hr · 150ms | ❓ |
| 4 | OpenAI gpt-4o-transcribe | 74 | ● 70 | 99 | ● 85 | ● 90 | $0.003/min mini | ⚠️ |
| 5 | gpt-realtime-whisper | 72 | ● 70 | 99 | ● 92 | ● 88 | $0.017/min streaming | ⚠️ |
| 6 | Gemini 3.1 Flash STT | 70 | ● 68 | 90 | ● 88 | ● 86 | ~$0.005–0.01/min | ⚠️ |
| # | Model | Maker | Score | Arena Elo | Text in image | Arabic text | Prompt adh. | Speed | $/image | Open? | Conf. |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | GPT Image 2 (high) | OpenAI | 93 | 1339 | ● 99 | ● 95 | ● 92 | ● 75 | $0.211 (high) · $0.053 (med) | No | ✅ |
| 2 | Reve 2.0 | Reve | 84 | 1281 | ● 88 | ● 60 | ● 88 | ● 82 | $0.024 · $0.04 edit | No | ⚠️ |
| 3 | MAI-Image-2.5 | Microsoft | 83 | 1271 | ● 85 | ● 60 | ● 86 | ● 80 | ~$0.02–0.06 (token) | No | ⚠️ |
| 4 | GPT Image 1.5 (high) | OpenAI | 82 | 1260 | ● 90 | ● 82 | ● 86 | ● 75 | $0.16 (high) | No | ✅ |
| 5 | Qwen-Image 2.0 | Alibaba | 82 | 1180 | ● 92 | ● 88 | ● 88 | ● 78 | ~$0.05 (varies) | Yes | ✅ |
| 6 | HiDream-O1-Image 1.5 | HiDream | 81 | 1265 | ● 84 | ● 58 | ● 88 | ● 80 | credit-based | Yes | ⚠️ |
| 7 | Cosmos3-Super | NVIDIA | 80 | 1227 | ● 78 | ● 55 | ● 80 | ● 78 | Free (open, self-host) | Yes | ⚠️ |
| 8 | Gemini 3.1 Flash Image | 80 | 1170 | ● 85 | ● 70 | ● 86 | ● 90 | $0.067 (1K) · $0.101 (2K) | No | ✅ | |
| 9 | HunyuanImage 3.0 | Tencent | 80 | 1152 | ● 88 | ● 85 | ● 88 | ● 80 | Free (open 80B MoE) | Yes | ✅ |
| 10 | Ideogram 4.0 | Ideogram | 79 | 1200 | ● 96 | ● 60 | ● 90 | ● 82 | $0.03 · $0.06 · $0.10 | Partial | ⚠️ |
| 11 | Imagen 4 Ultra | 79 | 1150 | ● 80 | ● 68 | ● 88 | ● 60 | $0.06 · $0.02 Fast | No | ⚠️ | |
| 12 | Seedream 5.0 Lite | ByteDance | 78 | 1150 | ● 80 | ● 58 | ● 84 | ● 88 | $0.031 + $0.007 web | No | ⚠️ |
| 13 | CogView-4 | Zhipu | 78 | 1180 | ● 82 | ● 45 | ● 88 | ● 80 | $0.03 · Apache 2.0 | Yes | ⚠️ |
| 14 | FLUX.2 Pro | Black Forest Labs | 77 | 1140 | ● 80 | ● 55 | ● 86 | ● 85 | $0.03–0.073 | Partial | ✅ |
| 15 | Grok Imagine 1.5 | xAI | 72 | 1173 | ● 70 | ● 55 | ● 78 | ● 85 | $0.02 | No | ❓ |
| 16 | Luma Photon | Luma Labs | 70 | 1100 | ● 72 | ● 50 | ● 82 | ● 92 | $0.015 · $0.002 Flash | No | ❓ |
| # | Model | Maker | Score | Max resolution | Max duration | $/clip | Open? | Conf. |
|---|---|---|---|---|---|---|---|---|
| 1 | CogVideoX-1.5 | Zhipu | 72 | 768×1360 | ~10s @ 16fps | Open (self-host) | Yes | ⚠️ |
| 2 | CogVideoX | Zhipu | 70 | 1440×960 | ~30s | Open (self-host) | Yes | ✅ |
| 3 | Ying (Qingying) | Zhipu | 68 | 1440×960 | ~6s clips | CN market · n/a | No | ⚠️ |
| Factor | Weight % | Tier |
|---|---|---|
| Hallucination level (low = better) | 16 | critical |
| Following instructions exactly | 11 | high |
| Document generation quality | 9 | high |
| Long task stamina | 9 | high |
| Tool use / agent reliability | 8 | high |
| Coding quality — real software | 7 | medium |
| Skills / tools per conversation | 7 | medium |
| Research & web browsing | 7 | medium |
| Hard reasoning / problem solving | 5 | medium |
| Image / chart understanding | 5 | medium |
| Cost — input + output | 4 | lower |
| Knowledge depth (PhD-level) | 4 | lower |
| Frontend / web design | 3 | lower |
| Coding — long projects | 3 | lower |
| Math accuracy | 1 | lower |
| Memory — claimed max | 1 | lower |
| Factor | Weight % | Tier |
|---|---|---|
| How natural it sounds (Egyptian) | 22 | critical |
| Pronunciation accuracy (Egyptian) | 18 | critical |
| Emotion & expressiveness | 12 | high |
| Voice cloning quality | 12 | high |
| Real-time conversation (S2S) | 10 | high |
| Steerability (tone control) | 8 | medium |
| Speed to first word | 7 | medium |
| Speech-to-text included | 5 | medium |
| Cost | 4 | lower |
| Voice variety | 2 | lower |
AI leaders and their capital cycle — capex commitments alongside the month’s market moves.
(23 Oct) SK Hynix shares rose after the chipmaker halted its review of plans to take its Solidigm storage unit public in the U.S. The decision comes amid broader market volatility in the semiconductor and AI infrastructure sectors.
Read full article → CNBC(24 Oct) A rotation out of AI stocks has prompted investors to adjust their portfolios, benefiting several defensive holdings. The shift reflects growing concerns over the sustainability of current AI funding levels.
Read full article → CNBC(23 Oct) Analysts argue that fears regarding AI agents disrupting the banking industry and bank deposits are currently overblown. The sector's underlying fundamentals remain resilient despite the technological shift.
Read full article → CNBC(24 Oct) Block introduced a new voice model capable of running locally on a MacBook M4 Max. The company noted that the model produces audio that sounds remarkably human.
Read full article → TechCrunch(23 Oct) OpenAI is close to finalizing a new funding round led by UAE investors to bridge its path to a 2027 IPO. The round is intended to provide substantial capital ahead of the public offering.
Read full article → CNBC(23 Oct) The U.S. operator of TikTok is seeking to secure multiple gigawatts of computing capacity over the coming years. The company has sounded out various opportunities to meet its growing infrastructure needs.
Read full article → CNBC(24 Oct) Stock slumps, pulled IPOs, and rising credit default swap spreads are creating pressure for neocloud providers ahead of hyperscaler earnings. The market turmoil highlights growing credit risks in the AI infrastructure buildout.
Read full article → CNBC(24 Oct) As Nvidia transitions from a pure chipmaker to an industry financier, investors are scrutinizing the outsized risk it is taking on tied to the AI buildout. The company's financial commitments to neoclouds are facing their first major market test.
Read full article → CNBC