A practical map of the 2026 migration: what people switched to, what each option costs, and what you give up.
· llmdeal.me
Spring 2026 broke the Claude lock-in that had held since 2024.
The immediate causes are well-documented elsewhere: peak-hour throttling that collapsed $200/month Max sessions to ~19 minutes, a token-drain bug (March 23–26) that ate a full weekly quota on a single prompt, an April quality regression confirmed by Anthropic's own postmortem, and the April 4 policy that made third-party tools like Cline, Roo Code, and Aider bill at per-token API rates on top of any subscription. By May, Vibe Kanban was reporting Claude Code's tool-usage share had dropped from 83% to 70%.
The interesting question is not why people left. It's where they actually landed — and what it costs them to stay there.
The most common immediate switch. Not the cheapest, but the most friction-free.
A dev.to analysis of 500 Reddit developers found that 65.3% preferred Codex over Claude Code by direct count; weighted by upvotes, that gap widens to 79.9% vs. 20.1%. The most-cited reason is blunt: "Claude Code is higher quality but unusable. Codex is slightly lower quality but actually usable."
Codex's practical cost advantage is also real on a per-token basis. Three benchmarked tasks showed Claude Code consuming 3.2–4.2x more tokens than Codex for equivalent output — a Figma plugin (6.23M vs. 1.49M tokens), a React/Node app (234.7K vs. 72.5K), and a REST API (~650K vs. ~180K). Even if your subscription price is the same, your effective throughput is very different.
On May 13, 2026, OpenAI accelerated the dynamic by offering 2 free months of Codex (valued at $3,000–$18,000 for enterprise tiers) to businesses switching within 30 days. Microsoft's Experiences & Devices division — reportedly canceling "thousands" of Claude Code employee licenses with a June 30 cutoff — is routing developers to GitHub Copilot CLI ($10/month), which is a different product but the same vendor direction.
The honest tradeoff with Codex: you get reliability and token efficiency, you lose the specific quality ceiling Claude Opus holds on complex reasoning tasks. For developers doing day-to-day feature work rather than hard architecture problems, that trade is increasingly easy to make.
The architectural move that makes every subsequent decision cheaper.
Anthropic's April 4 policy — which charged per-token API rates for any tool that isn't Claude Code or Claude.ai — had an unintended effect: it made the case for model-agnostic tooling self-evident. If you're already paying API rates, you might as well route to whichever API is cheapest.
Four tools dominate this space now:
The catch with BYOK tools is that API costs are unbounded. One Reddit user reported $200/month in Claude API bills while using Cline. The switch from subscription to API changes the risk profile — you trade a hard monthly cap for a variable bill that scales with usage. That's fine if you route deliberately; it's expensive if you don't.
Kilo Code takes a middle path: Apache 2.0, 500+ model support, zero markup on model costs via its Kilo Pass plan (from $19/month), or a KiloClaw subscription at $49/month for bundled access.
The option most Western developers haven't fully mapped yet.
A category of subscription plans from Chinese AI providers — GLM (Zhipu AI), MiniMax, Kimi (Moonshot AI), and Qwen (Alibaba Cloud) — positions itself as a drop-in replacement for Claude Code subscriptions at 1/7th to 1/65th the price. These plans expose OpenAI-compatible endpoints and work with Cursor, Cline, and any tool that accepts a custom base URL.
| Provider | Model | Tier | Price/month | Requests per 5h window |
|---|---|---|---|---|
| GLM (Zhipu AI) | GLM-5, GLM-4.7 | Lite | $3 | ~80 prompts |
| GLM (Zhipu AI) | GLM-5, GLM-4.7 | Pro | $15 | ~400 prompts |
| GLM (Zhipu AI) | GLM-5, GLM-4.7 | Max | $49 | ~1,600 prompts |
| Kimi (Moonshot AI) | Kimi K2.5 | Code Membership | ~$7/week | 300–1,200 calls |
| Qwen (Alibaba Cloud) | Qwen3.5-Plus, Qwen3-Coder, Kimi K2.5, GLM-4.7, MiniMax M2.5+ | Lite | $10 | 1,200 req / 9,000/week |
| Qwen (Alibaba Cloud) | Same multi-model pool | Pro | $50 | 6,000 req / 45,000/week |
Note: one secondary source (apiyi.com) cites GLM Lite at ~$9/month rather than $3, suggesting a tier or regional pricing difference — treat the lower figure as a floor rather than a guarantee. Kimi's weekly billing (~$7/week) means roughly $28–$30/month if used continuously, which inverts the "cheapest" pitch. Verify current pricing on each provider's own page before committing.
The capability claim that circulates most for GLM-5.1 is "94% of Claude Opus coding ability at 1/10th the cost." That comes from help.apiyi.com, a comparison site; treat it as indicative rather than an independent benchmark. What's clearer is that DeepSeek V4 hits 80.6% on SWE-bench Verified (vs. Claude Opus 4.6/4.7 at ~80.8%) at roughly $0.14/$0.28 per million input/output tokens — compared to Claude Opus at $3/$25. The API pricing gap is not ambiguous.
The tradeoff: these are subscription APIs with opaque SLAs, model versioning that may or may not match Western regulatory contexts, and latency that varies by region. For a developer working in the EU, data-residency questions apply. For someone who just needs to ship features without hitting walls, the maths are hard to argue with.
What most teams who stayed partly on Claude actually do.
The pattern that shows up repeatedly in 2026 developer writing is not a clean switch — it's tiered routing. Route 60–80% of agent traffic to a self-hosted or cheap-API open model; escalate the remaining 20–40% to a frontier API for the genuinely hard tasks. One analysis summarizes it: "The open-weight tier (Qwen 3 Coder, Kimi K2.6, DeepSeek weights) is now good enough that lots of teams run 60 to 80 percent of their agent traffic locally and only escalate the hard 20 percent to a frontier API."
Cursor Pro ($20/month with annual billing at $16/month) is the most popular IDE-layer implementation of this idea — it lets you point at Claude, GPT-5, or Gemini per-task without changing your workflow. Cursor has 3M+ weekly active users as of April 2026. Windsurf offers a similar multi-model approach at $15/month, though its pricing may have shifted following the 2026 Cognition acquisition — verify before committing.
The hybrid approach is the honest answer to "is local good enough?" It's not always. Local models achieve roughly 85–90% of Claude's quality on routine coding tasks, but on multi-file context work, Claude holds a meaningful quality lead. The financial case for local is clear above ~$500/month in cloud API spend: an RTX 4070 Ti Super at $489 pays back in 5–10 months. Below that threshold, hybrid API routing is usually cheaper than buying hardware.
The permanent exit from vendor lock-in, at a price.
Ollama (164,919+ GitHub stars, 112M+ pulls for Llama 3.1 alone) is the default runtime for local deployment. For pure coding tasks, the current local ceiling is around Qwen3.6-27B (dense, 77.2% SWE-bench Verified) or Qwen2.5-Coder-32B — both needing 24GB+ VRAM, both Apache 2.0 licensed. Throughput on consumer hardware is 15–25 tokens/second vs. 60–80 from the Claude API; for interactive use that's often fine, for large-scale agentic loops it starts to matter.
The economics at enterprise scale are unambiguous. One financial-services case study cut monthly AI spend from $45,000 to $12,000 (−73%) by migrating GPT-4 to self-hosted Llama 3.3 70B, with a $200,000 hardware investment that paid back in 4.5 months. A fintech example cut $47,000/month to $8,000 (−83%) using the same approach — keep frontier APIs for complex tasks, self-host for predictable workloads.
For individual developers, the case is less clean. A heavy Claude API habit runs $50–100/month in token costs. At that level, the $489 GPU pays back in 5–10 months — but only if local quality is genuinely sufficient for your work. That "if" is load-bearing.
| Destination | Approx. cost | What you gain | What you give up |
|---|---|---|---|
| OpenAI Codex / ChatGPT | $20/mo subscription | Reliable limits; 4x+ better token efficiency on typical tasks | Claude's quality ceiling on hard reasoning |
| Cline / Roo Code / Aider / OpenCode (BYOK) | Tool free; API pay-as-you-go | Model flexibility; route cheapest backend per task | Unbounded API bill if you don't route deliberately |
| GLM Lite (Zhipu AI) | $3/mo subscription | Lowest monthly price; CLI-compatible | Low request cap (~80 prompts per 5h); unverified independent benchmarks |
| Qwen Cloud Pro | $50/mo subscription | 6,000 req/5h; multi-model pool including Kimi and GLM | Data residency questions; SLA opacity vs. Anthropic/OpenAI |
| Hybrid routing (Cursor/Windsurf + cheap API) | $15–$20/mo IDE + API cost | Best of each model per task; familiar IDE | Config overhead; two billing relationships |
| Local (Ollama + Qwen3 / Qwen2.5-Coder) | $489 GPU, one-time (payback 5–10 mo) | Zero rate limits; zero per-token cost; full privacy | 15–25 tok/s throughput; 85–90% quality on routine tasks; upfront hardware cost |
The common thread: most developers did not switch to a single replacement. They split traffic. Routine work goes to the cheapest adequate option; genuinely hard tasks escalate to whatever frontier model currently earns that call. A smart API router — one key, one endpoint, rules for which model gets which request — is the obvious infrastructure layer for that pattern, which is exactly what llmdeal.me is building.
Rates checked against providers' own pricing pages, May 2026. Article published 2026-05-16.