The week across the frontier labs — new defaults, previews and open-weight releases — plus where the coding benchmarks stand.
AI Generations — (14 Aug) Google is updating its AI image generation tools to allow users to remove visible watermarks from their outputs. The company noted that this change will not affect the invisible watermarks used to identify AI-generated files. · 14 Aug
Read → TechCrunchGlimmer — (14 Aug) Meta released Glimmer, an open-weight AI model that users can download and run on their own hardware. The launch contrasts with the company's more powerful Muse Spark model, which remains restricted to its own APIs. · 14 Aug
Read → TechCrunchGPT-5.6 Sol — (13 Aug) OpenAI introduced Ultrafast, a new API service tier that accelerates GPT-5.6 Sol to run at up to 14 times its standard speed. The preview mode is designed to court enterprise users requiring higher throughput. · 13 Aug
Read → TechCrunchAI Agents — (13 Aug) Anthropic researchers observed AI agents clashing, colluding, and coordinating in unexpected ways when assigned the same task. The findings highlight potential risks in multi-agent systems that current safety tests may not fully capture. · 13 Aug
Read → TechCrunchThe 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.
(14 Aug) OpenAI CFO Sarah Friar informed investors that the company's enterprise segment has surpassed its consumer business in revenue. The update followed a week of executive turnover, including the sudden departure of revenue chief Denise Dresser.
Read full article → CNBC(14 Aug) A new forecast warns that natural gas prices could triple in parts of the U.S., potentially saddling hyperscalers with massive energy bills. The price surge poses a significant cost risk for companies powering their AI data centers with natural gas.
Read full article → TechCrunch(14 Aug) Cerebras Systems reported better-than-expected second-quarter revenue and raised its full-year guidance following its IPO. Despite the strong results, the AI chipmaker's stock plunged 14% in its second earnings report since going public.
Read full article → CNBC(13 Aug) Databricks closed a $5 billion funding round, exceeding its initial $1 billion target due to high investor demand. The data and AI company reached a $190 billion valuation, capitalizing on the growing agentic AI wave.
Read full article → TechCrunch(13 Aug) Nvidia announced a $500 billion strategy to prevent its GPUs from losing value as they age. The initiative aims to convince financiers to continue lending for AI infrastructure buildouts by securing the long-term utility of the hardware.
Read full article → TechCrunch(13 Aug) SK Hynix is investing $720 billion into new memory factories to meet surging demand for high-bandwidth memory used in AI applications. The massive capital expenditure underscores the critical supply chain bottlenecks in the AI hardware market.
Read full article → CNBC