--- title: Google’s next Gemini Pro is months behind schedule as... description: Google is months behind schedule on its next Gemini Pro model, primarily because coding capabilities have failed to meet internal benchmarks. A late-June... canonical: https://daily.dev/posts/google-s-next-gemini-pro-is-months-behind-schedule-as-coding-capabilities-fall-short-of-internal-goa-e7zidvmfs twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Google’s next Gemini Pro is months behind schedule as coding capabilities fall short of internal goals | daily.dev og:description: Google is months behind schedule on its next Gemini Pro model, primarily because coding capabilities have failed to meet internal benchmarks. A late-June... og:url: https://daily.dev/posts/google-s-next-gemini-pro-is-months-behind-schedule-as-coding-capabilities-fall-short-of-internal-goa-e7zidvmfs og:image: https://api.daily.dev/og/posts/E7ziDVMFs.png og:image:alt: Google’s next Gemini Pro is months behind schedule as coding capabilities fall short of internal goals og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Google’s next Gemini Pro is months behind schedule as coding capabilities fall short of internal goals **[The Next Web](https://daily.dev/sources/tnw)** · 3 min read · 16 upvotes · 6 comments ## Summary Google is months behind schedule on its next Gemini Pro model, primarily because coding capabilities have failed to meet internal benchmarks. A late-June training data refresh intended to boost coding performance disappointed internally. Structural issues — with Google Cloud, DeepMind, and Android teams all building competing AI coding tools — have slowed progress. OpenAI and Meta have released models that further outpace Google's current offerings in code generation. The delays have triggered a wave of senior engineer departures to Anthropic, driven by frustration with Google's competitive position. Sergey Brin has pushed for faster AI coding progress but faces internal resistance. Google says 75% of its code is now AI-generated and has consolidated developer tooling under an internal platform called Antigravity. Customers report mixed results with the current Flash model, with some switching to Anthropic. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Why is Google delaying the next Gemini Pro release? Google's upgraded Gemini Pro has fallen short of internal coding benchmarks and remains behind models from Anthropic and OpenAI, according to Bloomberg reporting citing ten current and former employees. A late training data refresh aimed at improving coding failed to deliver expected gains, and internal competition between Google Cloud, DeepMind, and Android teams building separate AI coding tools has slowed unified progress, despite Sergey Brin pushing for faster shipping. _Developers picking a coding model can track how Gemini, Claude, and GPT stack up on daily.dev._ ### How does Google's current Gemini Flash model compare to Anthropic's Claude for coding tasks? Reactions are mixed: Figma's product manager said Flash hit a good balance of speed and quality for their AI assistant, while Platzi's CEO said Flash is slower and more expensive than its predecessor and far less capable than competitors, leading his team to switch to Anthropic's Claude instead. _Teams weighing Gemini against Claude for coding can compare real user experiences on daily.dev._ ## Community discussion Top comments from developers on daily.dev. **@hardik15** · 6 upvotes > Based on current situation Gemini will have utmost pressure, as I have rarely seen anyone using Gemini for coding. > > > May be in few years google turn the tide, however till then they have to wait and improve. **@elmarchavez** · 2 upvotes > The advantage of Google as a company is its stability, consistency, and a huge amount of resources. If they could manage a slow and steady progress, it could outlast any leading AI companies to date. **@keen** · 1 upvotes > they focused too much in small weight model and they're good, with the Gemma 4 and all. **@lucasayabe** · 1 upvotes > its sad to see Google so far behind, they have by far the best ecosystem in AI companies, there's no product close to what NotebookLM is and their recent integration with Google Chrome is quite good much better than Opera or Brave ones **@kartiknvj** · 0 upvotes > The detail that a training-data refresh was needed to move coding scores says the bottleneck is eval and data quality, not raw scale. Coding is one of the few capabilities with a hard pass/fail signal, so it exposes regressions the softer benchmarks hide. Makes me wonder if "months behind" is really months spent building better coding evals rather than training runs. --- Tags: [#llm](https://daily.dev/tags/llm), [#openai](https://daily.dev/tags/openai), [#ai-coding](https://daily.dev/tags/ai-coding), [#anthropic](https://daily.dev/tags/anthropic), [#google-gemini](https://daily.dev/tags/google-gemini) [View this post on daily.dev](https://daily.dev/posts/google-s-next-gemini-pro-is-months-behind-schedule-as-coding-capabilities-fall-short-of-internal-goa-e7zidvmfs) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Google’s next Gemini Pro is months behind schedule as coding capabilities fall short of internal goals","url":"https://daily.dev/posts/google-s-next-gemini-pro-is-months-behind-schedule-as-coding-capabilities-fall-short-of-internal-goa-e7zidvmfs","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/google-s-next-gemini-pro-is-months-behind-schedule-as-coding-capabilities-fall-short-of-internal-goa-e7zidvmfs"},"datePublished":"2026-07-16T20:21:43.603Z","dateModified":"2026-09-14T08:56:57.939Z","description":"Google is months behind schedule on its next Gemini Pro model, primarily because coding capabilities have failed to meet internal benchmarks. 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If they could manage a slow and steady progress, it could outlast any leading AI companies to date.","datePublished":"2026-07-17T10:18:30.904Z","url":"https://daily.dev/posts/E7ziDVMFs#c-NU3Ujyzim","author":{"@type":"Person","name":"Elmar Chavez","url":"https://daily.dev/elmarchavez","image":"https://media.daily.dev/image/upload/s--7PjH979T--/f_auto/v1780994221/avatars/avatar_bK85rJb2OXXID2LX2wi5y?_a=BAMAMiWQ0"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":2}},{"@type":"Comment","text":"they focused too much in small weight model and they’re good, with the Gemma 4 and all.","datePublished":"2026-07-17T08:23:01.038Z","url":"https://daily.dev/posts/E7ziDVMFs#c-qdcyLf7aF","author":{"@type":"Person","name":"Keanu Kent Gargar","url":"https://daily.dev/keen","image":"https://media.daily.dev/image/upload/f_auto/v1645286608/avatars/tuAS1pyYMt8aWgWVL3u15"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1}},{"@type":"Comment","text":"its sad to see Google so far behind, they have by far the best ecosystem in AI companies, there’s no product close to what NotebookLM is and their recent integration with Google Chrome is quite good much better than Opera or Brave ones","datePublished":"2026-07-17T06:35:55.365Z","url":"https://daily.dev/posts/E7ziDVMFs#c-rwAOvsFVl","author":{"@type":"Person","name":"Lucas Ayabe","url":"https://daily.dev/lucasayabe","image":"https://lh3.googleusercontent.com/a-/AOh14Ght1VAD_wMUn2QGKCYw3wYXfC3HWT68UDbvk2dP5Q=s100"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1}},{"@type":"Comment","text":"The detail that a training-data refresh was needed to move coding scores says the bottleneck is eval and data quality, not raw scale. Coding is one of the few capabilities with a hard pass/fail signal, so it exposes regressions the softer benchmarks hide. Makes me wonder if “months behind” is really months spent building better coding evals rather than training runs.","datePublished":"2026-07-17T13:36:18.165Z","url":"https://daily.dev/posts/E7ziDVMFs#c-E1PF8hhhe","author":{"@type":"Person","name":"kartik-nvjk","url":"https://daily.dev/kartiknvj","image":"https://media.daily.dev/image/upload/s--3gGgsVCw--/f_auto/v1781456774/avatars/avatar_TvTVeiMdkRCqWUDullFmy?_a=BAMAMiWQ0"}}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/google-s-next-gemini-pro-is-months-behind-schedule-as-coding-capabilities-fall-short-of-internal-goa-e7zidvmfs#faq","mainEntity":[{"@type":"Question","name":"Why is Google delaying the next Gemini Pro release?","acceptedAnswer":{"@type":"Answer","text":"Google's upgraded Gemini Pro has fallen short of internal coding benchmarks and remains behind models from Anthropic and OpenAI, according to Bloomberg reporting citing ten current and former employees. 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