Benchmark
A composite benchmark that scores large language models across multiple evaluations into one comparative intelligence rating from Artificial Analysis.
Xiaomi's $850,000 and $2.62 million cover 30 reinforcement-learning steps apiece on models it had already pretrained. Xiaomi published the environments and the RL code but not the 7,000-plus task datasets behind them.
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Artificial Analysis measured the score itself, and the weights are on Hugging Face under MIT, but MiMo-V2.6-Pro holds 1.02 trillion parameters, so most teams will reach it through an API at $0.43 per million input tokens.
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Google priced Gemini 4 Argon at half Claude Opus 5.5's per-token rate for a model one composite index ranks third, behind two Anthropic models. On price alone it only matches OpenAI's newly discounted GPT-6.1 Sol, so the price edge Google is selling is against Anthropic.
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Grok 4.7 keeps Grok 4.6's $2/$6 token price yet costs $3.74 per task against $1.86, by Artificial Analysis' measurement. Teams that budget from the price sheet will undercount agent spend until they measure tokens per task on their own work.
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Google's Gemini 4 Argon tied GPT-6 Astra and Claude Fable 5.1 at 53 on the Artificial Analysis index, though some Google staff say its coding lags. Google disputes them, and until paid API access has a date, buyers cannot check the score on their own code.
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Google's Gemini 4 Argon matches GPT-6.1 Sol's $2/$10 token price but costs 2.7 times as much per task, according to Artificial Analysis. Argon uses more tokens per job, so buyers still have to compare frontier models by cost per completed task.
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Mistral AI raised 3 billion euros in a Series D led by Samsung Electronics, at a post-money valuation above 21 billion euros. Buyers who choose it for data residency get a label that covers where models run, on an API priced at 11 to 19 times the open-model median.
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Google's Gemini 3.8 Flash ties Claude Opus 5 at 74% on DeepSWE for $2.36 a task, at an introductory price that doubles on January 1, 2027. For agent workloads, the comparison that holds up after January is cost per finished task, set by steps taken as much as by rate.
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Alexandr Wang says the new model costs developers no more than 1.2 and finishes the same work on about a quarter fewer tokens. That is a real saving on high-volume code generation and a rounding error most other places.
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Meta's fourth Muse Spark in five months gains four points on Artificial Analysis' Intelligence Index, almost entirely in agentic tests, while two scores fall and the tier Meta benchmarked against rivals is still a limited preview.
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V4.1-Flash retires the V4 Pro line and carries two active-parameter counts, 763B total with 8B on input tokens and 16B on output, so one sizing number no longer covers both phases of a request. Baseten had it running on day zero.
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Artificial Analysis scores the new Xiaomi model first among open weights and twelve points behind Claude Opus 5.5, and the cheaper Flash tier is the one an operator should put in front of a real queue.
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Z.ai's 320-billion-parameter model activates 18 billion per token and ships under MIT, so a buyer can download it and measure for themselves. Every capability figure published so far comes from Z.ai's own launch materials.
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Cloudflare says its graph model flagged eight malicious scripts running on live storefronts. A retrospective check put seven of the eight outside VirusTotal entirely. URLScan flagged none of the eight as malicious.
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Alibaba's 27B scores 52 on the Artificial Analysis index from a 17GB quantized file. Filling its 262,144-token window needs roughly 16 GiB of KV cache on top of that, so the file size is the smaller half of the sizing question.
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The calculator prices its featured coding workload at about $6.94 a month through OpenRouter against 26 cents of electricity. The machine is still $3,419 down after a year and 7.97 billion tokens from break-even.
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Korea's Dokpamo program gives the benchmarking firm's index 25 of the 100 points that decide which teams advance. In the results published on August 27, the team that led that component finished last of the four.
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The model string keeps working after the cutover, so a pinned request comes back from V4.1-Flash. By the figures in the dev.to write-up, that model scores 90.6 on Terminal-Bench 2.1 and 42.3 on SimpleQA, against V4-Pro's 55.2.
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Sarah Friar told Goldman Sachs' technology conference that a pricier model can be cheaper when it needs fewer tries, a claim Artificial Analysis puts at an eleven-to-one price spread against seven index points running the other way.
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DeAlignAI's downloadable FP8 build is the license working exactly as written, while its self-reported 320-of-320 HarmBench run remains unchecked by any outside researcher and measures compliance, not capability.
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Invest · September 4, 2026 · One report1 publisher
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