TL;DR — In one week (April 20–23, 2026), four frontier coding models shipped: Kimi K2.6 (Moonshot, Apr 20), GPT-5.5 (OpenAI, Apr 23), DeepSeek V4 Pro + V4 Flash (preview, April). Claude Opus 4.7 is still the SWE-Bench Pro champion. Kimi K2.6 is the new cost/quality winner at $0.60/$4.00 (ties GPT-5.5 on SWE-Bench Pro, 10× cheaper). DeepSeek V4 Flash at $0.14/$0.28 with 1M context is the new baseline workhorse. This is a reference, not an essay — use the tables, skip the prose.
The one table that matters
| Model | Input $/M | Output $/M | Context | SWE-Bench Pro | When to use | |---|---:|---:|---:|---:|---| | Claude Opus 4.7 | $15 | $75 | 200K | 64.3% 🥇 | Subtle codebase edits, reasoning under ambiguity, Claude Code plan mode | | GPT-5.5 | $5 | $30 | 1M | 58.6% | Agent loops, terminal workflows, long-reasoning memos | | DeepSeek V4-Pro | $1.74 | $3.48 | 1M | ~55% | Plan + hard debug + refactor at 1/10 Opus cost | | Kimi K2.6 | $0.60 | $4.00 | 256K | 58.6% | Long-horizon agentic coding, multi-file refactors | | GPT-5.4 | $2.50 | $15 | 1.05M | 57.7% | Mid-budget high-reliability tool calls | | Claude Sonnet 4.6 | $3 | $15 | 200K | ~54% | Workhorse — best Anthropic tool-call reliability | | DeepSeek V4-Flash | $0.14 | $0.28 | 1M | ~47% | Implementation, test generation, docs at near-zero cost | | Claude Haiku 4.5 | $1 | $5 | 200K | ~35% | Docs, small edits, classifier calls | | GPT-5 Mini | $0.25 | $2 | 400K | ~40% | Small edits, cheap fallback |
The 30-second decision tree
Is quality the ONLY thing that matters?
├─ Yes → Opus 4.7 (if budget allows) or GPT-5.5 (if 1M context matters)
└─ No, cost matters too:
│
Is it long-horizon agentic (50+ turns, multi-file)?
├─ Yes → Kimi K2.6 (best coherence per dollar)
└─ No:
│
Is the task reasoning-heavy (plan, debug, review)?
├─ Yes → DeepSeek V4-Pro (cheapest reasoner at Opus-ish quality)
└─ No → DeepSeek V4-Flash (writes correct code at $0.14/M)
What actually changed this week
Kimi K2.6 (Apr 20, Moonshot) — biggest cost/quality shift
- Open-weight MoE, 1T params / 32B active, 256K context
- 58.6% SWE-Bench Pro = tied with GPT-5.5
- Trained specifically for 300-sub-agent / 4,000-step trajectories
- 10× cheaper than GPT-5.5, 25× cheaper than Opus 4.7
- Cache hit: $0.16/M (73% off)
- Full review
Headline: at $0.60/$4.00, it's the first open-weight model that doesn't force a quality compromise on real coding agents.
GPT-5.5 (Apr 23, OpenAI) — best reasoner, not best coder
- 1M context, Artificial Analysis Intelligence Index 60 (new leader)
- Terminal-Bench 2.0: 82.7% (vs GPT-5.4's 75.1%)
- SWE-Bench Pro: 58.6% — still behind Opus 4.7 (64.3%) on real-world edits
- Pricing doubled vs 5.4: $5 / $30 standard, Pro tier $30 / $180
- Full review vs Opus 4.7
Headline: huge leap on agentic/terminal workflows, modest gain on real code patching. Opus 4.7 still wins the coding crown but loses the cost race.
DeepSeek V4 Pro + Flash (April, DeepSeek)
- V4-Pro: $1.74 / $3.48, 1M context, 81% SWE-bench Verified (near Opus territory)
- V4-Flash: $0.14 / $0.28, 1M context, replaces old
deepseek-chatmapping - Both support tool calls, JSON, thinking mode
- Cache-hit discounts are aggressive (Flash 80% off, Pro 92% off)
- Full Pro vs Flash comparison
Headline: two products, not one. Pin Flash for routine implementation + test; escalate to Pro for plan/debug/refactor where reasoning pays.
GPT-5.4 (already out, recalibrated vs 5.5)
- $2.50 / $15, 1.05M context
- Unified Codex + GPT line — best OpenAI tool-call reliability
- 33% fewer hallucinated facts vs GPT-5.2
- Now positioned as OpenAI's mainstream mid-tier below the premium GPT-5.5
By-task cheat sheet
Planning / architecture — Opus 4.7 ≈ GPT-5.5 ≈ V4-Pro · Don't send to V4-Flash
Implementation (write new code from spec) — V4-Flash or K2.6 · Don't pay for Opus/GPT-5.5 here
Debug — Opus 4.7 > GPT-5.5 > V4-Pro > K2.6 · Reasoning matters, don't skimp
Test generation — V4-Flash > K2.6 > Sonnet 4.6 · Pure bargain territory
Refactor (multi-file) — V4-Pro ≈ K2.6 > Sonnet 4.6 · 1M context or K2.6's agent coherence
Docs / docstrings — Haiku 4.5 ≈ Gemini 3 Flash ≈ GPT-5 Mini · Sub-$1 territory, don't overspend
Agent loops (Claude Code, Aider, Cline) — GPT-5.5 ≈ K2.6 > Sonnet 4.6 · Step stability matters most
The monthly bill math
Same 30M-token workload (typical solo heavy user):
| Strategy | Monthly cost | |---|---:| | 100% Opus 4.7 | ~$990 | | 100% GPT-5.5 | ~$330 | | 100% Sonnet 4.6 | ~$198 | | 100% K2.6 | ~$48 | | 100% V4-Flash | ~$6 | | Phase-routed (plan→Opus, agent→GPT-5.5, impl/test→V4-Flash, refactor→K2.6) | ~$25–40 |
The 100%-flagship scenarios are wasteful on routine work. The 100%-cheap scenarios break on hard reasoning. Phase-routing wins on both axes.
What's obsolete now
- DeepSeek V3.2 — auto-replaced by V4-Flash via the
deepseek-chatalias. Legacy only. - Kimi K2.5 — K2.6 is strictly better on every axis except nostalgia.
- GPT-5.2 — kept in registries for historical usage-log compatibility; don't default to it in 2026+.
- GPT-4o — already retired February 2026.
What's still the right answer
- Claude Haiku 4.5 — unchanged, still the Anthropic cheap workhorse at $1/$5
- Gemini 3 Pro / Flash — complementary, not displaced, especially for vision + 1M-context reads
- Claude Sonnet 4.6 — still the most reliable tool-calling model and the default workhorse for Anthropic-pinned workflows
Using all four at once
Pinning any single model to your coding agent in April 2026 is objectively the wrong move. Four frontier-tier models released in one week with different cost/quality trade-offs. The right setup:
- Point your coding agent (Claude Code, Aider, Cursor, OpenClaw, Cline, Continue, Windsurf) at a phase-aware router.
- Router detects the coding phase (plan / implement / debug / test / refactor / docs / small-edit) and routes to the optimal model per-call.
- Single API key. Single invoice. 10× cheaper than pinning any flagship.
That's what CodeRouter does. Setup takes two environment variables:
export ANTHROPIC_BASE_URL="https://api.coderouter.io/v1"
export ANTHROPIC_AUTH_TOKEN="cr_..."
Want manual model pinning at provider list-price × 1.15? Direct plan — one $10 top-up gets you access to all 18 models including claude-opus-4-7, gpt-5.5, deepseek-v4-pro, and kimi-k2.6, billed per-request against a prepaid balance.
The verdict
If you read nothing else:
- New default for routine coding: DeepSeek V4-Flash ($0.14/$0.28, 1M context, auto-upgraded from the old
deepseek-chatID). - New default for long-horizon agents: Kimi K2.6 ($0.60/$4.00, 256K, agent-swarm native).
- Reach for Claude Opus 4.7 when SWE-Bench Pro quality (sensitive codebase edits) specifically matters.
- Reach for GPT-5.5 for terminal-workflow agent loops where 82.7% Terminal-Bench matters.
- Don't pay GPT-5.5 prices for work a $0.14 model can do — use a phase-aware router.