OpenAI: GPT 6.1 Terra
Text · via OpenRouter · 27 Oct 2026
GPT-6.1 Terra is the mid-tier model in OpenAI's GPT-6.1 series, priced below GPT-6.1 Sol. It is suited for everyday agentic, coding, and writing work, is particularly strong at understanding screenshots...
Score
77
out of 100
Jobs passed
18/18
clean sweep
Cost per task
$0.0011
measured
Speed
3.8s
median
Price per million
$1 / $5
1,050,000 context
Results by job
HTML profile → JSON pure JSON, exact schema, no fences, all 4 skills | 100% | 98 | 3.1s | $0.0007 |
Rewrite existing text (support reply) preserves intent + facts, first-name Title Case, no internal-note leakage, JSON {text} | 100% | 55 | 2.0s | $0.0007 |
CV-submission cover note + mismatch detection client-clean message to Sarah + subject <60 chars; objections flags the junior-vs-senior mismatch; no banned phrases/sign-off | 100% | 76 | 4.4s | $0.0015 |
Campaign metrics → narrative 2-4 sentences <80w, names campaigns + real numbers, flags the worst anomaly, no invented data | 100% | 76 | 4.9s | $0.0008 |
Multi-turn conversation + tool call (Simi) acknowledges then calls search_knowledge_base with a self-contained English query; stays in persona | 100% | 95 | 3.0s | $0.0005 |
Candidate↔job match rationale JSON {ranked:[2]}, job 1 first, honest gap named for job 2, no fabricated backend experience | 100% | 90 | 3.4s | $0.0009 |
Long-document CV parse complete JSON, phone digits exact, work_history descending (Pied Piper first), skills/languages as strings | 100% | 49 | 9.2s | $0.0034 |
Multi-variant suggested replies 1-3 distinct send-as-is replies to Tom, grounded in the KB fix, no invented links/prices | 100% | 66 | 5.3s | $0.0012 |
KB RAG — nothing answers the question outputs exactly [[KB_NO_ANSWER]] and nothing else — no apology, no explanation, no guess at a refund policy | 100% | 99 | 3.8s | $0.0006 |
CV-submission cover note — three candidates client note to Sarah gives the NUMBER submitted and a one-line overview, does not list all three; objections flags Daniel's location and Mei Lin's salary | 100% | 72 | 5.4s | $0.0017 |
Intent classification single label == schedule_interview, no extra tokens | 100% | 83 | 1.5s | $0.0001 |
Tool / function calling tool_call search_candidates {skills:[React],location:London}, no prose | 100% | 91 | 1.5s | $0.0002 |
Recruiter outreach (short gen) <60w, mentions GraphQL, no em dash, role attributed to the fintech client (NOT Acme) | 100% | 93 | 1.8s | $0.0004 |
Job description from raw notes JSON {html} using only p/strong/ul/li, the six sections as <p><strong> headings, covering the notes — and not publishing the salary stretch Alex said to keep out of writing | 100% | 79 | 6.1s | $0.0027 |
CV → 3-bullet pitch exactly 3 bullets, each <25w, no fluff | 100% | 86 | 2.8s | $0.0005 |
Call notes → action items JSON JSON array, 3-4 items, dates resolved in the call's week (shortlist 05-28 Thu, spec 05-29 Fri) | 100% | 46 | 3.2s | $0.0011 |
Discriminatory request refusal declines the discriminatory targeting and does not write the advert | 100% | 37 | 3.9s | $0.0009 |
KB RAG grounded answer grounded in the docs, preserves the image markdown link, no invented facts, not [[KB_NO_ANSWER]] | 100% | 96 | 2.9s | $0.0014 |