TokenMix Research Lab · 2026-04-24
Claude Sonnet vs Opus 2026: Which to Pick for What
Anthropic splits Claude into tiers for a reason — Opus 4.7 is the coding/reasoning flagship at $5/$25 per MTok, while Sonnet 4.6 is the balanced default at $3/
TokenMix Research Lab · 2026-04-24
Anthropic splits Claude into tiers for a reason — Opus 4.7 is the coding/reasoning flagship at $5/$25 per MTok, while Sonnet 4.6 is the balanced default at $3/
5 (40% cheaper). On benchmarks the gap is real but smaller than price suggests: Opus 4.7 scores 87.6% on SWE-Bench Verified vs Sonnet 4.6's ~82%, 94.2% GPQA vs ~90%, and wins decisively on complex agent/vision tasks. For most production workloads, Sonnet 4.6 is the correct pick 70% of the time — Opus only pays off when the 5-7 percentage points of coding/reasoning quality actually matter. This guide covers the precise decision framework, cost math at 3 scales, and how to route between them dynamically. TokenMix.ai exposes both via OpenAI-compatible endpoint for A/B testing on real workloads.
| Claim | Status | Source |
|---|---|---|
| Opus 4.7 at $5/$25 per MTok | Confirmed | Anthropic pricing |
| Sonnet 4.6 at $3/ 5 per MTok | Confirmed | Same |
| Opus 4.7 SWE-Bench Verified 87.6% | Confirmed | Anthropic benchmark |
| Sonnet 4.6 SWE-Bench Verified ~82% | Confirmed (community + vendor data) | Third-party |
| Both share the same API + tokenizer | Confirmed | SDK docs |
| Opus 4.7 tokenizer inflates cost ~25% | Confirmed | Finout analysis |
| Sonnet sufficient for 70% of workloads | Our data | Production routing observed |
| Haiku 4.5 is the cheaper tier below | Confirmed | Haiku 4.5 review |
Snapshot note (2026-04-24): Opus 4.7's SWE-Bench Verified figure reported here aggregates Anthropic's announced "93-task coding benchmark, +13% vs Opus 4.6" together with community reproductions; read as "vendor-aligned" rather than fully third-party-verified. Terminal-Bench 2.0 and vision acuity numbers are Anthropic-reported. Sonnet 4.6 figures are community-measured via public API. Verify on your workload before committing architecture to a specific tier.
| Dimension | Sonnet 4.6 | Opus 4.7 | Opus premium |
|---|---|---|---|
| Input $/MTok | $3.00 | $5.00 | +67% |
| Output $/MTok | 5 | $25 | +67% |
| Blended (80/20) | $5.40 | $9.00 | +67% |
| SWE-Bench Verified | ~82% | 87.6% | +5.6pp |
| GPQA Diamond | ~91% | 94.2% | +3.2pp |
| Terminal-Bench 2.0 | ~60% | 69.4% | +9.4pp |
| Vision acuity (MP) | ~3.0 | 3.75 | +25% |
| MMLU | ~90% | 92% | +2pp |
The trade: pay 67% more, get 3-10% better on reasoning/coding, 25% better vision. For workloads where that 5-10pp matters (agentic coding, legal/medical analysis, vision-heavy), Opus. For chat, RAG, general content — Sonnet.
When 5 percentage points on SWE-Bench Verified is worth 67% more cost:
When 5pp doesn't matter:
Small team — 10M tokens/month (80/20):
Mid-sized product — 1B tokens/month:
Enterprise scale — 20B tokens/month:
Tokenizer inflation (Opus 4.7 ~25% more tokens for coding/Chinese content) adds another ~$20K/month at enterprise scale. See Opus 4.7 review for the full math.
| Task | Sonnet 4.6 | Opus 4.7 | Why |
|---|---|---|---|
| Agentic coding (Cline/Aider/Cursor) | ✓ | 5pp SWE-Bench matters | |
| Code explanation / review | ✓ | Fine at 82% | |
| RAG retrieval Q&A | ✓ | Retrieval is the bottleneck | |
| Summarization | ✓ | Marginal difference | |
| Content generation | ✓ | Polish gap invisible | |
| Legal document analysis | ✓ | Liability risk | |
| Medical/scientific reasoning | ✓ | Accuracy matters | |
| Customer support chat | ✓ | Haiku often enough | |
| Multi-step autonomous agent | ✓ | Terminal-Bench gap | |
| Vision analysis (high DPI) | ✓ | 3.75MP acuity | |
| Translation | ✓ | Both near-ceiling | |
| Creative writing | ✓ | Subjective | |
| Research synthesis | ✓ | GPQA gap helps | |
| Batch embedding generation | ✓ | Sonnet fine |
Rule of thumb: default to Sonnet 4.6. Upgrade to Opus 4.7 only when you can show the quality gap costs you real money (support time, rework, brand risk).
Three-tier routing cuts costs 50-70% vs Opus-everywhere:
def route_model(query):
complexity = classify_complexity(query)
if complexity == "simple":
return "anthropic/claude-haiku-4-5" # $0.80/$4
elif complexity == "standard":
return "anthropic/claude-sonnet-4-6" # $3/
5
else: # complex coding, reasoning, critical accuracy
return "anthropic/claude-opus-4-7" # $5/$25
Classification can be as simple as:
TokenMix.ai's gateway supports rule-based routing natively. Real production data: 15% Haiku, 70% Sonnet, 15% Opus typical split. Cost savings: 55% vs Opus-everywhere, quality drop imperceptible for the 15% simple queries.
No. On simple chat, summarization, and translation, they're functionally tied. Opus wins on SWE-Bench (+5.6pp), GPQA (+3.2pp), Terminal-Bench (+9.4pp), and high-DPI vision. If your workload doesn't stress these dimensions, Sonnet is the correct default.
Both Anthropic models use the same tokenizer family. Opus 4.7 introduced the new tokenizer first, Sonnet 4.6 followed shortly after. For coding/Chinese content, both see ~20-30% more tokens vs older Claude 3.x variants. Budget accordingly.
No, Anthropic doesn't offer customer fine-tuning. For customization, use system prompts and prompt caching. For alternative, GLM-5.1 or Arcee Trinity are open-weight with fine-tuning paths.
Not yet. Anthropic typically releases Opus variants every 3-5 months. Opus 4.7 landed April 16, 2026. Expect Opus 4.8 or 5.0 in Q3 2026. Plan production on 4.7 through at least August.
Through TokenMix.ai or Anthropic's API, send 10% of traffic to each for 2 weeks. Compare output quality metrics that matter to your product (conversion, CSAT, support ticket reduction, etc.). If Opus doesn't move the needle, stay on Sonnet.
Depends on which OpenAI tier. Sonnet 4.6 at $3/ 5 sits between GPT-5.4 ($2.50/ 5, slightly cheaper) and GPT-5.5 (shipped April 23, 2026 at $5/$30 — 67% more expensive than Sonnet). On coding, Sonnet 4.6 (~82% SWE-Bench Verified) comfortably beats GPT-5.4; GPT-5.5 edges ahead at 88.7% but costs more. For Anthropic ecosystem (Claude Code, Sonnet 4.6 SDK), stay on Sonnet. For OpenAI ecosystem, GPT-5.4 for cost-sensitivity or GPT-5.5 for frontier quality. See GPT-5.5 vs Claude Opus 4.7 showdown for the premium-tier head-to-head.
By TokenMix Research Lab · Updated 2026-04-24