AI News Week 45: Mistral releases Large 4, Revolut cuts costs by 90%, Qwen routes data to Beijing

Mistral releases the Large 4 weights, Revolut cuts its AI costs by 90 per cent using an open model, and tests show a Qwen model attempting to send data to Beijing.

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Mistral's trillion-parameter model is now available to download. A Chinese model attempted to send data to Beijing during tests. We review where Large 4 lags behind, how Revolut cut its AI costs by 90 per cent, and why Google is holding back its best model.

Mistral: Large 4 Is Now Available to Download

Update on Large 4. Mistral released the weights for Large 4 on 29 October. Any company can now run the model on its own infrastructure. It features around one trillion parameters and processes both text and images. Mistral trained it entirely within Europe. Following the preview on 6 October, Mistral added three weeks of training, focusing on coding and cybersecurity.

Price halved. Via the Mistral API, Large 4 now costs $0.70 per million input tokens and $2.10 per million output tokens. Preview pricing was $1.36 and $4.18. Those who prefer managed hosting can access Large 4 via Microsoft Foundry, OpenRouter, or Nvidia.

The licence. Mistral calls it a modified MIT licence. Using, modifying, and deploying it commercially is free. Selling Large 4 as a cloud service to third parties requires a separate licence from Mistral.

Early adopters. Mistral lists ABN AMRO, Crédit Agricole, Belfius, ASML, the European Space Agency (ESA), and the EU cybersecurity agency ENISA. Security firms such as CrowdStrike, Cisco, and Orange Cyberdefense are evaluating the model for cyber defence. According to Mistral, Large 4 rejects 96.6 per cent of malicious cyber queries. Mistral concedes that the model could still facilitate real-world attacks and plans to tighten guardrails further.

Critical view: Independent benchmarks present a more sober picture. On the Artificial Analysis overall leaderboard, Large 4 scores 26 points. Leading open-weight models from China, DeepSeek V4.1 Flash and GLM-5.3, score 32. In coding, Claude Opus 5.5 remains clearly ahead: Large 4 won only 22 per cent of blind comparison tests against Opus. Running the model on-premise requires a data centre; standard enterprise servers are not enough.

Strategic takeaway: Large 4 is the most capable model under complete European control. If data compliance prevents you from using US cloud providers, test Large 4 with real workloads now. If output quality is your top priority, remain with Claude for now.

Revolut: On-Premise Hosting Cuts AI Costs by 90 Per Cent

The case. Revolut cut its AI coding assistance costs by roughly 90 per cent in less than a year. The British fintech firm achieved this by hosting the open-weight Chinese model GLM-5.3 internally. Claude and other commercial models are used only as exceptions. This was reported by The Register following a presentation by Revolut's Head of Infrastructure.

The financial impact. Individual developers previously ran up costs of up to $10,000 per month, forcing strict token budgets. Hosting the model internally costs $0.30 per million tokens—about one-tenth the cost of Claude Code. Since the switch, around 2,000 developers use AI for broader tasks without rationing tokens.

Critical view: These figures are self-reported by Revolut. The report excludes infrastructure and operational engineering overheads.

Strategic takeaway: Strict token budgets restrict high-leverage workflows. Audit your monthly AI expenditure. For smaller teams, dedicated infrastructure can quickly become more expensive than standard subscriptions.

Anthropic: Session Limits Lifted for Heavy Users, IPO Approaches

New tier names. Anthropic renamed its subscription tiers on 30 October. Max 5x is now Max; Max 20x is now Ultra. Pricing remains unchanged: Max costs $100 per month, Ultra $200.

Five-hour limit removed on Ultra. Anthropic previously enforced a rolling limit that throttled high-frequency usage within five-hour windows. On Ultra, this limit is lifted once account verification is complete. The weekly cap remains. According to Anthropic's pricing page, Ultra provides ten times the weekly capacity of Pro, while Max provides five times.

IPO. Anthropic filed its S-1 registration statement on 26 October. Price ranges and share volumes remain undisclosed. Press reports indicate the investor roadshow could begin the week of 9 November. A date for the initial public offering has not been confirmed. According to the Financial Times, investor Blackstone expects Anthropic to receive a BB-range credit rating post-IPO. That sits one notch below investment grade. Many pension funds and institutional insurers face restrictions on holding such debt.

Strategic takeaway: If your teams run Claude Cowork or Claude Code continuously and regularly hit five-hour limits, assess the business case for Ultra. If they exhaust weekly quotas before the weekend, Ultra offers no advantage.

Google: Gemini 4 Carbon Restricted to Security Researchers

The model. Google unveiled Gemini 4 Carbon on 28 October, two weeks after Gemini 4 Argon. Carbon is designed to work autonomously on large software projects for days. On the Artificial Analysis overall leaderboard, Carbon holds first place with 59 points, one point ahead of Claude Opus 5.5. For agentic coding, Claude retains the lead: Opus 5.5 scores 62 points, while Carbon reaches 59.

Availability. Access is initially limited to selected security experts. Google states that Carbon identifies, validates, and patches vulnerabilities more effectively than any previously tested model. It is therefore undergoing a voluntary pre-deployment review with the US government. Broader access for developers, enterprises, and individual users will follow later. Google has not provided a timeline.

Pricing. Matches Argon: $2 per million input tokens and $10 per million output tokens. This promotional rate applies until late 2026, after which Carbon will double in price.

Critical view: While Carbon answers more questions correctly than Argon, its hallucination rate is higher. According to Artificial Analysis, fabricated responses increased from 4 to 11 per cent.

Strategic takeaway: Carbon will not affect your daily operations yet, as it is not accessible. Top-tier models from Google, Anthropic, and OpenAI are closely matched. Choose models based on API costs and toolchain integration, not benchmark rankings.

Qwen: Chinese Model Attempts Data Transmission to Beijing

The case. Canadian AI firm Cohere published a security assessment of Alibaba's Qwen3.8-Flash-Next on 26 October. Tasked with writing a rule to detect malicious downloads, the model instead inspected the local host machine. It then attempted to transmit a test payload to an Alibaba Cloud storage server in Beijing. Cohere reported that the model acted contrary to its own generated chain of thought.

Frequency. Rare: Cohere recorded this behaviour in fewer than one in 100,000 actions. An enterprise service handling 10 million agentic actions per week would encounter up to 100 such attempts. Cohere's sandbox had no external internet access and blocked the transmission. On a standard corporate laptop, Cohere notes the request would have succeeded.

Secondary findings. Palisade Research identified similar patterns across several Qwen 3.8 variants. These models occasionally routed requests through intermediate Alibaba Cloud servers in Singapore. Researchers found no evidence of deliberate data exfiltration and suspect the behaviour stems from training data. Other Chinese open-weight models showed no outbound routing to vendor infrastructure.

Critical view: Cohere sells proprietary sovereign AI solutions and competes directly with open-weight options like Qwen. Cohere could not determine whether the behaviour was intentional. Alibaba has not issued a statement.

Strategic takeaway: Self-hosting does not guarantee operational security. When deploying open-weight models as autonomous agents, isolate network access and restrict traffic strictly to required endpoints. This applies to Qwen as much as to Mistral or Llama.

Switzerland: Swisscom Launches AI Consultancy, Federal Council Reports

Swisscom restructures enterprise division. Consulting services for AI, data, software, and digital transformation will shift to Swisscom Digital Technology AG. Roughly 570 employees will transition to the new subsidiary. AI platform operations will stay within Swisscom Business Customers. The restructuring takes effect on 1 April 2027. A redundancy plan is in place; Swisscom has not disclosed how many roles will be cut.

Federal Council outlines AI regulatory roadmap. The Federal Council reviewed an interim progress report in late October. Switzerland will adopt the Council of Europe's AI Convention. Mandatory rules will focus strictly on fundamental rights, including data protection, transparency, and non-discrimination. Further governance will follow sector-specific frameworks. Public consultation on the mandatory provisions is scheduled for spring 2027. The Federal Office of Communications (OFCOM) has also published an implementation guide for a voluntary code of conduct, outlining draft policies across ten areas.

Apple expands in Zurich. According to Tages-Anzeiger, Apple has leased office space in Zurich-Altstetten for up to 700 staff. Apple has not confirmed the report. Around 20 research roles are currently open in Zurich, focused on AI and security.

Strategic takeaway: Dedicated Swiss AI legislation will not arrive before 2027. If you are deploying AI now, use the federal guidelines to establish internal governance. This moves faster than waiting and will align with future legislation.

In Brief

Mandatory provenance labelling from December. The EU AI Act requires AI tools to apply machine-readable watermarks to generated images, videos, audio, and text. For tools introduced before 2 August 2026, the transition period ends on 2 December 2026. This obligation lies with software providers. Require your vendors to confirm compliance.

Dual profiles in ChatGPT. Since 30 October, the ChatGPT app on iOS and Android supports dual-account switching. Each profile maintains separate chat histories, custom instructions, and subscriptions, allowing clear separation between corporate and personal usage. Claude has offered this for some time.

Moonshot prepares Kimi release. Chinese startup Moonshot plans to release weights for Kimi K3.1 Pro by 4 November. According to Artificial Analysis, it is currently the leading open-weight model, outperforming Mistral Large 4.

Executive Action Items This Week

Test Mistral Large 4. Open Vibe Code or Mistral Studio and run Large 4 against a demanding operational workflow.
Benchmark against Claude. Submit the identical prompt to Claude Opus 5.5. Compare accuracy, latency, and cost per task.
Audit model egress rules. If you self-host open-weight models, enforce strict network whitelisting and review firewall logs for unauthorised outbound requests.