MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
Model Comparison · Head to Head

GPT-5.5 vs GPT-5.6 Terra

GPT-5.5 wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorOpenAI / OpenAI
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose GPT-5.5 when coding depth, long-context reliability matter most; choose GPT-5.6 Terra when lower cost, lower latency is the priority.

Choose GPT-5.5 if you…

  • Balanced with no weak spot
  • Richest ecosystem
  • Mature plugin/function calling
  • Strong creative writing
  • Best for: General tasks, Creative writing, Coding

Choose GPT-5.6 Terra if you…

  • OpenAI quality
  • Halved price
  • Rich ecosystem
  • Best for: Value, General tasks, OpenAI ecosystem
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.

GPT-5.5 Higher overall
OpenAI · #5 overall
Overall81
Coding75
Multimodal85
VS
GPT-5.6 Terra
OpenAI · #21 overall
Overall62
Coding70
Multimodal69

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionGPT-5.5GPT-5.6 TerraVerdict
VendorOpenAI (US)OpenAI (US)Same vendor
Released2026.042026.07GPT-5.6 Terra is newer
Overall (rank)81 · #562 · #21GPT-5.5 +19
Coding75 · #870 · #12GPT-5.5 +5
Multimodal85 · #869 · #19GPT-5.5 +16
Context window1.05M1.05MTie
Max output128K128KTie
Effective-context9088GPT-5.5 more reliable
Input $/1M$5$2.5GPT-5.6 Terra cheaper
Output $/1M$30$15GPT-5.6 Terra cheaper
Cache discount50% off50% offTie
Speed~50 tok/s~60 tok/sGPT-5.6 Terra faster
TTFT0.8s0.5sGPT-5.6 Terra snappier
Function calling9590GPT-5.5 ahead
Refusal rate~15%~13%GPT-5.6 Terra less restrictive
English9488GPT-5.5
Chinese7672GPT-5.5
Modalitiestext, imagetext, imageSame
Open weightsNoNoBoth closed
Fine-tuningYesNo
Free tierChatGPT free tier available (rate-limited); Plus $20/monthNo free API
SOC2 / no-trainyes / yesyes / yes
Private deploymentNoNoNeither

Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

GPT-5.5 leads the overall aggregate by 19 points (81 vs 62). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while GPT-5.6 Terra remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a modest gap: GPT-5.5 scores 75 against 70. On multi-file edits, SWE-style tickets and long-horizon agent loops GPT-5.5 needs fewer correction turns; GPT-5.6 Terra is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

GPT-5.5 leads multimodal 85 vs 69. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

GPT-5.6 Terra is faster in interactive use: ~60 tok/s with 0.5s TTFT versus ~50 tok/s with 0.8s TTFT (about 1.2× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1.05M for GPT-5.5 and 1.05M for GPT-5.6 Terra. Effective-context scores point the same way as window size — GPT-5.5 is ahead on usable recall (90 vs 88), so prefer it for long-document work where details cannot be missed.

Price & total cost

GPT-5.6 Terra is the cheaper API at $2.5/$15 versus GPT-5.5 at $5/$30 per 1M input/output tokens — list input is about 2.0× lower. Cache discounts (GPT-5.5 50% vs GPT-5.6 Terra 50%) shift the effective bill, worked out below.

Chinese vs English

English: GPT-5.5 94 vs GPT-5.6 Terra 88. Chinese: 76 vs 72. Both are US-based models; for Chinese-first workloads also compare domestic models on the leaderboard.

Tool use & ecosystem

Function-calling score: GPT-5.5 95 vs GPT-5.6 Terra 90, so GPT-5.5 has the edge on structured tool use. Fine-tuning is available from GPT-5.5. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthGPT-5.5GPT-5.6 TerraGap
List priceno cache applied$1,400100M in × $5  +  30M out × $30$700100M in × $2.5  +  30M out × $152.00×gap
With caching90% of inputs cache-hit$1,17590M cached in × $2.5  +  10M in × $5  +  30M out × $30$58890M cached in × $1.25  +  10M in × $2.5  +  30M out × $152.00×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose GPT-5.5 (coding 75 vs 70).
IF you serve real-time users and latency is a product KPI  →  choose GPT-5.6 Terra (~60 tok/s, 0.5s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose GPT-5.6 Terra ($$2.5/$$15 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose GPT-5.5 (effective context 90 vs 88).
07

Frequently asked questions

Is GPT-5.5 worth the higher price over GPT-5.6 Terra?
At list the input rate is 2.0x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when GPT-5.5's stronger dimensions protect revenue; for routine volume GPT-5.6 Terra is the economical pick.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, GPT-5.5 is about $1,175/month and GPT-5.6 Terra about $588/month after cache discounts ($1,400 and $700 at list).
Does the bigger context window actually matter?
Nominal windows are GPT-5.5 (1.05M) and GPT-5.6 Terra (1.05M), but usable recall follows the effective-context score (90 vs 88). Prefer the higher effective-context model for long-document work where nothing can be missed.
Is GPT-5.5 worth choosing over GPT-5.6 Terra within OpenAI?
Both come from OpenAI. GPT-5.5 is the vendor's higher tier (81 vs 62 overall) and is the pick when you want this lab's strongest model; GPT-5.6 Terra costs less and remains the sensible choice where its score already clears the bar.
Which one supports fine-tuning?
GPT-5.5 supports fine-tuning; GPT-5.6 Terra does not at this tier. If you plan to adapt the model to a narrow domain, that is a concrete differentiator.
Which handles multimodal inputs better?
Multimodal scores are 85 (GPT-5.5) vs 69 (GPT-5.6 Terra), with modality coverage text/image versus text/image. Match the model to the input types your product actually receives.