AI performance
Latest stories covering AI performance, with summaries and links to related coverage.
2 stories · 2 reports · page 1 of 1
1 story · 1 report in the last 7 days
Latest report · Counts as of (UTC)
Models in this coverage
Up to six tracked models linked to this topic’s reports in the last 30 days. Counts measure coverage on Themata, not usage.
- Claude Opus 5.5
Anthropic
· Closed
Anthropic’s model for complex reasoning and longer agent tasks. Built for work such as large codebase changes, code review, and multi-step problem solving.
1 story · 1 report on this topic
- DeepSeek V4.1 Flash
DeepSeek
· Open weights
An open-weight mixture-of-experts model that reads text and images. Its architecture focuses on efficient long-context and agent workloads, with support for up to one million tokens.
1 story · 1 report on this topic
Connected topics
Topics connected through shared stories across the archive.
Latest stories
Mistral Large 4
tool
11 min read
Mistral has launched a public-preview API for Mistral Large 4, a natively multimodal mixture-of-experts model with 1 trillion total parameters and 52 billion active parameters. The company plans to release its open weights by the end of the month. Mistral Large 4 was trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral-operated European data centers, using multilingual data spanning more than 160 languages. The preview API is available through Mistral Studio, priced at $1.36 per million input tokens and $4.18 per million output tokens. Mistral says the model is its largest and most capable release, targeting coding, tool-using agents, cybersecurity, finance, law, science, and visual understanding. It reported scores of 82% on a vulnerability reproduction-and-patching test, 93% on Cybench security challenges, 61.7% on DeepSWE v1.1, 59.9% on AutomationBench, and 42% on Dense 200 visual grounding. Mistral also said ML4 resists 93.3% of attacks in Lakera’s B3 AI Security Benchmark. Before the weight release, Mistral is red-teaming the model with cybersecurity leaders, vetted partners, and state authorities that will receive reduced moderation and expanded cyber capabilities. The company says ML4 can be self-deployed in private clouds or on premises and will underpin specialized future Mistral models. Its development is funded in part by Mistral’s €3 billion Series D round.
DeepSeek V4.1 Flash 1017 (Max)
research
5 min read
DeepSeek released the reasoning model DeepSeek V4.1 Flash 1017 (Max) on October 17, 2026. The open-weights model accepts text and image inputs, produces text, and supports a 1 million-token context window. It is a mixture-of-experts model with 552 billion total parameters and 16 billion active parameters during inference. Its weights are available on Hugging Face under the MIT license, which permits commercial use, and it is available through five API providers. Artificial Analysis gave the model a score of 45 on its Intelligence Index, compared with a median score of 19 among open-weight models of a similar size. The composite index evaluates reasoning, knowledge, mathematics and coding. The evaluation generated 210 million output tokens, above the comparable-model median of 140 million, indicating relatively high verbosity. DeepSeek’s API pricing is $0.30 per million input tokens and $1.20 per million output tokens, below respective comparison medians of $0.43 and $1.68. Artificial Analysis estimates an average Intelligence Index evaluation cost of $0.26 per task. Output speed measured 230.4 tokens per second, compared with a 77.9-token-per-second median, while time to first token was 1.08 seconds versus a 1.69-second median.