Model comparison
Claude Sonnet 5 vs GPT-5.6 Terra
Anthropic against OpenAI, compared on context, price, and verified benchmark results.
Catalog record checked August 12, 2026; individual provider fields may change.
Anthropic
Claude Sonnet 5
Balanced
OpenAI
GPT-5.6 Terra
Balanced
| Specification | Claude Sonnet 5 | GPT-5.6 Terra |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Tier | Balanced | Balanced |
| Context window | 1M | Winner: 1.05M |
| Max output | 128K | 128K |
| Input / 1M tokens | $2 | $2 |
| Output / 1M tokens | Winner: $10 | $12 |
| Weights | Closed | Closed |
| Parameters | Not disclosed | Not disclosed |
| Reasoning levels | low, medium, high, xhigh, max | none, low, medium, high, xhigh, max |
| Modalities | text, image | text, image |
| Released | June 30, 2026 | July 9, 2026 |
| Artificial Analysis Intelligence Index [max] (2026-08-08) | 55 | Winner: 57 |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Pricing tiers: Claude Sonnet 5: List price is $2/$10 per million input/output tokens. Anthropic made the launch intro rate the standard price; the previously scheduled 2026-09-01 step to $3/$15 will not occur. · GPT-5.6 Terra: Prompts above 272K tokens bill at 2× input and 1.5× output; cache writes are 1.25× the input rate.
Claude Sonnet 5
Anthropic's mid tier on paper, though its DeepSWE cost per completed task is the highest recorded here.
Best for
- Everyday generation
- Short, well-scoped tasks
Watch out
Cheaper per token than Opus 5 but $26.40 per DeepSWE task against Opus 5's $11.84 — it used 214K output tokens over 268 steps.
GPT-5.6 Terra
OpenAI's middle tier, balancing capability against cost.
Best for
- Mixed workloads
- Teams standardising on one model
Watch out
10x Luna's input price; check whether Luna already suffices for the workload.
Benchmark
DeepSWE 1.1 in context
Both models shown against the wider field, with cost per completed task alongside the score.
Local leader
Claude Opus 5 [max]
74%
Rows shown
24
Highest published reasoning effort per model (not best Pass@1)
Snapshot date
2026-08-13
Mirrored from deepswe.datacurve.ai
Better is toward the top-right (higher pass rate, lower cost). X-axis is reversed to match DeepSWE’s public chart. v1.1 uses average cost / tokens / steps; v1 uses published medians.
| # | Model | Pass@1 | Cost / task | Tokens / task | Steps / task |
|---|---|---|---|---|---|
| 1 | Claude Opus 5 [max] | 74% | $11.84 | 118k | 99 |
| 2 | GPT-5.6 Sol [max] | 73% | $8.39 | 60k | 61 |
| 3 | Claude Fable 5 [max] | 70% | $21.63 | 119k | 88 |
| 4 | GPT-5.6 Terra [max] | 70% | $4.95 | 72k | 76 |
| 5 | Kimi K3 [max] | 69% | $4.65 | 82k | 98 |
| 6 | GPT-5.6 Luna [max] | 67% | $3.03 | 73k | 102 |
| 7 | GPT-5.5 [xhigh] | 67% | $7.23 | 46k | 82 |
| 8 | Grok 4.6 [xhigh] | 67% | $5.50 | 71k | 87 |
| 9 | Gemini 3.7 Flash [high] | 65% | $2.18 | 107k | 125 |
| 10 | DeepSeek V4-Pro [max] | 63% | $0.24 | 106k | 155 |
| 11 | Claude Opus 4.8 [max] | 59% | $13.22 | 135k | 120 |
| 12 | Qwen3.8-Max [xhigh] | 58% | $3.73 | 95k | 111 |
| 13 | Muse Spark 1.2 [xhigh] | 55% | $3.70 | 99k | 101 |
| 14 | Claude Sonnet 5 [max] | 54% | $26.40 | 214k | 268 |
| 15 | Grok 4.5 [high] | 54% | $2.42 | 36k | 61 |
| 16 | DeepSeek V4-Flash [max] | 53% | $0.10 | 108k | 153 |
| 17 | Muse Spark 1.1 [xhigh] | 53% | $2.36 | 74k | 96 |
| 18 | GPT-5.4 [xhigh] | 52% | $5.65 | 71k | 70 |
| 19 | Gemini 3.6 Flash [high] | 47% | $4.42 | 96k | 117 |
| 20 | GLM 5.2 [max] | 44% | $3.92 | 78k | 129 |
| 21 | Gemini 3.5 Flash [high] | 36% | $3.45 | 76k | 105 |
| 22 | Kimi K2.7 Code | 31% | $2.82 | 59k | 149 |
| 23 | Claude Sonnet 4.6 [high] | 30% | $5.52 | 76k | 134 |
| 24 | Gemini 3.1 Pro [high] | 12% | $2.14 | 28k | 76 |
DeepSWE “Best” picks the highest published reasoning effort per model (not the highest pass rate). Small gaps may not be statistically meaningful — confirm on deepswe.datacurve.ai.
Common questions
Claude Sonnet 5 vs GPT-5.6 Terra
Answered from the verified figures on this page rather than general guidance.
Is Claude Sonnet 5 or GPT-5.6 Terra cheaper for input?
Both cost $2 per million input tokens at standard rates, so input price is not a deciding factor between them.
Is Claude Sonnet 5 or GPT-5.6 Terra cheaper for output?
Claude Sonnet 5 is cheaper at $10 per million output tokens, against $12 for GPT-5.6 Terra — roughly 1.2× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Claude Sonnet 5 has tiered pricing: List price is $2/$10 per million input/output tokens. Anthropic made the launch intro rate the standard price; the previously scheduled 2026-09-01 step to $3/$15 will not occur. GPT-5.6 Terra has tiered pricing: Prompts above 272K tokens bill at 2× input and 1.5× output; cache writes are 1.25× the input rate.
Which has the larger context window, Claude Sonnet 5 or GPT-5.6 Terra?
GPT-5.6 Terra accepts 1.05M tokens against 1M for Claude Sonnet 5. This only matters if you routinely send very long documents or large codebases.
Do Claude Sonnet 5 and GPT-5.6 Terra support the same reasoning levels?
Claude Sonnet 5 exposes low, medium, high, xhigh, max, while GPT-5.6 Terra exposes none, low, medium, high, xhigh, max.
Should I use Claude Sonnet 5 or GPT-5.6 Terra?
Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. Claude Sonnet 5 suits everyday generation; GPT-5.6 Terra suits mixed workloads.
Next step
Choosing between them
Tier and workload decide this more reliably than a leaderboard position does.
If both sit in the same tier, the decision usually comes down to context window and output price rather than headline capability — output tokens dominate real bills.
If one is a step up within the same provider, the useful question is whether your hardest task actually fails on the cheaper tier. Most production volume — classification, extraction, summarization — does not.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Muse Code, or Lovable? Compare agentic harnesses · Latest releases.