AI Devtools Radar

Issue #3 · Aug 2, 2026 · week of Jul 26 – Aug 2

DeepSeek doubles peak-hour pricing, GitHub Copilot drops two Gemini models, mem0 fixes delete_all() leaving data behind

The radar watched 63 sources across 32 tools this window and published 32 changes; these are the ten worth your attention, ranked. Every item carries the before/after evidence the pipeline captured — expand it before you take our word.

  1. DeepSeek will charge 2x the regular price during peak hours (9:00–12:00 and 14:00–18:00 Beijing time) once the policy takes effect; no effective date yet. Batch jobs and anything latency-tolerant are worth shifting off-peak before the bill shows up.

    pricinghigh

    Peak/off-peak pricing policy coming to DeepSeek API service

    API pricing will increase to 2x during peak hours (9:00–12:00 and 14:00–18:00 Beijing Time, UTC+8) daily. This affects all billing items. Effective date pending official announcement.

    Evidence
    +(2) The DeepSeek API service will soon adopt a peak/off-peak pricing policy. During peak hours, prices will be 2x the regular prices, applicable to all billing items. The effective date will be subject to the official announcement. [Peak hours: 9:00–12:00 and 14:00–18:00 (Beijing Time, UTC+8) daily]

    api-docs.deepseek.com

  2. As of July 31, GitHub Copilot dropped Gemini 2.5 Pro and Gemini 3 Flash across Chat, inline edits, and agent mode. Copilot Enterprise admins need to enable Gemini 3.1 Pro (Preview) and Gemini 3.6 Flash through policy settings; anyone still pinned to the old names loses access outright.

    deprecationhigh

    Gemini 2.5 Pro and Gemini 3 Flash models deprecated in GitHub Copilot

    Users must migrate from Gemini 2.5 Pro to Gemini 3.1 Pro (Preview) and from Gemini 3 Flash to Gemini 3.6 Flash. Copilot Enterprise administrators need to enable alternative models through policy settings. Deprecated models no longer available in Copilot Chat, inline edits, ask/agent modes, and code completions.

    Evidence
    +As of today, July 31, 2026, we have deprecated the following models across all GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions). Gemini 2.5 Pro 2026-07-31 Gemini 3.1 Pro (Preview) Gemini 3 Flash 2026-07-31 Gemini 3.6 Flash

    github.blog · also seen at 1 more source

  3. The deepseek-chat and deepseek-reasoner model names were retired on July 24; both now map to deepseek-v4-flash's non-thinking and thinking modes. Code still calling the old names is running against a renamed model, not the one it was tested against.

    deprecationhigh

    deepseek-chat and deepseek-reasoner models deprecated with sunset date July 24, 2026

    API users using these legacy model names must migrate to deepseek-v4-flash before the deprecation date to avoid service disruption.

    Evidence
    deepseek-chat (to be deprecated on 2026/07/24) deepseek-reasoner (to be deprecated on 2026/07/24) * The model names deepseek-chat and deepseek-reasoner will be deprecated on 2026/07/24 15:59 UTC. For compatibility, they correspond to the non-thinking mode and thinking mode of deepseek-v4-flash, respectively.
    +model

    api-docs.deepseek.com · also seen at 1 more source

  4. The Anthropic provider in Vercel's AI SDK now reports thinking tokens under reasoning token usage instead of wherever they landed before. Anything reading token usage to track cost, quota, or reasoning-mode spend should recheck its math after upgrading.

    api

    Anthropic SDK now reports thinking tokens as reasoning token usage

    Developers using @ai-sdk/anthropic will see thinking tokens correctly categorized in token usage metrics, improving cost tracking and API usage visibility.

    Evidence
    +e29788d: fix(anthropic): report thinking tokens as reasoning token usage

    github.com

  5. OpenAI is replacing Priority Processing with Fast mode; existing Priority Processing traffic migrates automatically. Behavior should carry over, but anything hardcoded to the old name in docs, dashboards, or billing exports needs updating.

    positioning

    Priority processing renamed to Fast mode with updated performance positioning

    API users using priority processing will see their requests automatically migrated to the new Fast mode offering; branding change from 'Priority processing' to 'Fast mode'

    Evidence
    Priority processing
    +Fast mode We're also introducing Fast mode in the API, which replaces our Priority Processing offering.

    platform.openai.com

  6. mem0's Python delete_all() used to list the vector store once and stop, so accounts with more memories than a single page (most stores default to around 100) had the rest silently left behind. It now paginates in batches of 1000. Anyone who called delete_all() for compliance or privacy reasons before this fix should confirm the data actually left the store.

    apihigh

    Mem0 Python SDK: delete_all() now paginates through vector store in batches of 1000

    Accounts with more memories than a single page will now have all memories deleted correctly instead of silently leaving the remainder behind.

    Evidence
    +delete_all() now paginates through the vector store in batches of 1000 instead of listing once, so accounts with more memories than a single page (most vector stores default to ~100) had the remainder silently left behind

    github.com

  7. The Copilot app used to inherit its access rules from the Copilot CLI policy; it now has its own, with the same three options (enabled everywhere, disabled everywhere, or let organizations decide). Admins who disabled the CLI to keep the app off will find the app now needs its own policy set.

    featurehigh

    GitHub Copilot app now has a dedicated access policy separate from Copilot CLI

    Enterprise and organization administrators can now independently control access to the Copilot app through dedicated policies, with three options: Enabled everywhere, Disabled everywhere, or Let organizations decide. Gives more granular control over which Copilot clients teams can use.

    Evidence
    +The GitHub Copilot app now has its own policy, so you can control who has access to it at the enterprise and organization levels. Until now, access to the Copilot app depended on your GitHub Copilot CLI policy being enabled. From several conversations with customers, we understand that many of you want to manage each client independently. Now the Copilot app and the Copilot CLI each have their own policy, giving you the flexibility and control to enable the right clients for your teams.

    github.blog

  8. Neon now lets you grant access at the project level instead of only across the whole organization. If contractors or partial teams have had org-wide access purely because project scoping did not exist, that workaround is no longer necessary.

    featurehigh

    Project-level permissions feature released for Neon

    Users can now grant access at the project level instead of organization-wide, providing more granular access control and improved security for organizations managing multiple projects.

    Evidence
    +Project level permissions. A feature you've been asking for is finally here. Until now, a person's access applied across your entire organization.

    neon.com · also seen at 1 more source

  9. Vercel's AI Gateway can now pin requests to the US or EU with a single field, working across every provider behind the gateway, and returns the serving region on each response. Relevant if data residency rules have been blocking use of the gateway at all.

    featurehigh

    Regional inference now available on AI Gateway with US/EU pinning

    AI Gateway users can now control request routing to specific regions (US or EU) with a single field, providing better data residency control and performance optimization across all providers.

    Evidence
    +Regional inference now available on AI Gateway Pin requests to the US or EU with a single field that works across every provider, and get the serving region back on every response.

    vercel.com · also seen at 1 more source

  10. Kimi K3 is now priced on Together AI at $3.00 per million input tokens and $15.00 output, with a $0.30 cached-input rate. A concrete number to put next to whatever you are currently paying for a comparable model.

    pricinghigh

    Kimi K3 model pricing introduced with input/output rates and cache option

    Developers can now use Kimi K3 model on Together AI platform with $3.00 input cost and $15.00 output cost, plus a $0.30 cached option for inputs.

    Evidence
    +Kimi K3 $3.00 $0.30 (cached) $15.00

    www.together.ai

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