coding models

Z.ai has released GLM-5.3-Flash, a native multimodal model built for coding and long-horizon agent tasks, featuring a 1M-token context window and a hybrid sparse-linear attention architecture. The model is available via OpenRouter at a discounted $0.075/$0.25 per 1M tokens through September 2026.

Google released Gemini 3.7 Flash just three weeks after its predecessor, posting sharp gains on coding benchmarks while cutting launch pricing in half to $0.75 per million input tokens and $3.75 per million output tokens.

Google has released Gemini 3.7 Flash, just three weeks after Gemini 3.6 Flash, claiming substantial gains in coding, web development, and document reasoning. The model launches at an introductory price of $0.75 per 1M input tokens and $3.75 per 1M output tokens — half the cost of its predecessor.

Upstage has released Solar Pro 4, a large language model with a 524K token context window aimed at agentic workflows, document processing, and coding. The model is priced at $0.03 per million input tokens and $0.12 per million output tokens, and is available now via OpenRouter.

Alibaba announced Qwen3.8-Max, a 2.4T-parameter flagship model targeting coding and long-horizon agentic work, with open weights promised for next week alongside Qwen3.8-27B. The model posted strong third-party benchmark results, ranking #4 in Frontend Code Arena and matching Claude Opus 4.7 on the Vals Index at roughly 2.3x lower cost.

Anthropic has released Claude Opus 5, its new flagship model built for complex reasoning, coding, and multi-agent coordination. The model ships with a 1 million token context window and pricing of $5 per million input tokens and $25 per million output tokens.

Poolside has released Laguna S 2.1, a mixture-of-experts coding model with 8 billion active parameters out of 118 billion total, its third coding model release in three months. The company claims it outperforms open-weight models 10 to 20 times its size on agentic coding benchmarks like Terminal-Bench 2.1 and DeepSWE.

Moonshot AI's Kimi K3 model has claimed first place in the Code Arena frontend benchmark with a score of 1,679, surpassing Claude Fable 5 (1,631) and GPT-5.6 Sol (1,618). However, the model achieves only 39% accuracy on FrontierMath Tier 4, while top Western models from OpenAI and Anthropic reach near 90% on the same expert-level math tasks.

Beijing-based Moonshot AI released its Kimi K3 model Friday, which topped Arena's front-end coding capability rankings. The model is priced at half the cost of OpenAI's GPT-5.6 Sol, according to Bank of America research analysts, marking what Arena CEO calls "the single biggest release of the year."

OpenAI released GPT-5.6 in three variants: Sol ($5 input/$30 output per 1M tokens), Terra ($2.50/$15), and Luna ($1/$6). According to OpenAI, Sol achieves an 80-point score on the Artificial Analysis Coding Agent Index, 2.8 points above Anthropic's Fable 5, while using less than half the output tokens and costing one-third less.

Meta publicly released Muse Spark 1.1, a multimodal AI model designed for agentic coding workflows. The model is priced at $1.25 per million input tokens and $4.25 per million output tokens, positioning it slightly above Anthropic's Claude Haiku 4.5 and OpenAI's GPT-5.6 Luna.

Elon Musk's SpaceXAI has released Grok 4.5, priced at $2 per million input tokens and $6 per million output tokens. The model, trained alongside recently-acquired Cursor, is positioned as a coding and enterprise tool that claims to outperform Claude Opus 4.8 on several benchmarks while undercutting it on price by 60-76%.

xAI has released Grok Build 0.1, a coding-specialized model with a 256K context window and unlimited text output. The model is designed for agentic software engineering workflows and powers xAI's Grok Build CLI tool.

DeepSeek has released V4 Pro, a Mixture-of-Experts model with 1.6 trillion total parameters and 49 billion activated parameters. The model supports a 1-million-token context window and costs $1.74 per million input tokens and $3.48 per million output tokens.

Moonshot AI has released Kimi K2.6, an open-source multimodal model with 1 trillion total parameters (32B activated) and 256K context window. The model achieves 80.2% on SWE-Bench Verified, 58.6% on SWE-Bench Pro, and supports horizontal scaling to 300 sub-agents executing 4,000 coordinated steps.