MiniMax M3 vs GPT-5.6 Terra
MiniMax M3 wins on Overall, Multimodal; GPT-5.6 Terra wins on Coding. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.
Verdict at a glance
Choose MiniMax M3 if you…
- Strong agent ability
- Open source
- Low price
- Best for: AI agents, Open source, Chinese
Choose GPT-5.6 Terra if you…
- OpenAI quality
- Halved price
- Rich ecosystem
- Best for: Value, General tasks, OpenAI ecosystem
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.
Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.
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.
| Dimension | MiniMax M3 | GPT-5.6 Terra | Verdict |
|---|---|---|---|
| Vendor | MiniMax (CN) | OpenAI (US) | Different vendors |
| Released | 2026.06 | 2026.07 | GPT-5.6 Terra is newer |
| Overall (rank) | 70 · #13 | 62 · #21 | MiniMax M3 +8 |
| Coding | 68 · #13 | 70 · #12 | GPT-5.6 Terra +2 |
| Multimodal | 70 · #18 | 69 · #19 | MiniMax M3 +1 |
| Context window | 1M | 1.05M | GPT-5.6 Terra larger |
| Max output | 64K | 128K | MiniMax M3 longer |
| Effective-context | 90 | 88 | MiniMax M3 more reliable |
| Input $/1M | $0.6 | $2.5 | MiniMax M3 cheaper |
| Output $/1M | $2.4 | $15 | MiniMax M3 cheaper |
| Cache discount | none | 50% off | GPT-5.6 Terra deeper |
| Speed | ~60 tok/s | ~60 tok/s | Tie |
| TTFT | 0.5s | 0.5s | Tie |
| Function calling | 84 | 90 | GPT-5.6 Terra ahead |
| Refusal rate | ~7% | ~13% | MiniMax M3 less restrictive |
| English | 70 | 88 | GPT-5.6 Terra |
| Chinese | 88 | 72 | MiniMax M3 |
| Modalities | text | text, image | different coverage |
| Open weights | Yes | No | MiniMax M3 is open |
| Fine-tuning | Yes | No | |
| Free tier | Hailuo AI free; open-platform quota | No free API | |
| SOC2 / no-train | no / yes | yes / yes | |
| Private deployment | Yes | No | MiniMax M3 |
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.
Dimension-by-dimension analysis
Reasoning & overall intelligence
MiniMax M3 leads the overall aggregate by 8 points (70 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-5.6 Terra scores 70 against 68. On multi-file edits, SWE-style tickets and long-horizon agent loops GPT-5.6 Terra needs fewer correction turns; MiniMax M3 is still competent for scripts and assisted completion but trails as task complexity rises.
Multimodal
MiniMax M3 leads multimodal 70 vs 69. A concrete modality difference: GPT-5.6 Terra additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.
Speed & latency
MiniMax M3 is faster in interactive use: ~60 tok/s with 0.5s TTFT versus ~60 tok/s with 0.5s TTFT (about 1.0× 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 1M for MiniMax M3 and 1.05M for GPT-5.6 Terra. Crucially, the larger nominal window does not win on usable recall: GPT-5.6 Terra advertises 1.05M but MiniMax M3 scores higher on effective-context (90 vs 88), i.e. it actually retains more of what it was given.
Price & total cost
MiniMax M3 is the cheaper API at $0.6/$2.4 versus GPT-5.6 Terra at $2.5/$15 per 1M input/output tokens — list input is about 4.2× lower. Cache discounts (GPT-5.6 Terra 50%) shift the effective bill, worked out below.
Chinese vs English
English: MiniMax M3 70 vs GPT-5.6 Terra 88. Chinese: 88 vs 72. For Chinese-language production, MiniMax M3 is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.
Tool use & ecosystem
Function-calling score: MiniMax M3 84 vs GPT-5.6 Terra 90, so GPT-5.6 Terra has the edge on structured tool use. Fine-tuning is available from MiniMax M3. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.
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 month | MiniMax M3 | GPT-5.6 Terra | Gap |
|---|---|---|---|
| List priceno cache applied | $132100M in × $0.6 + 30M out × $2.4 | $700100M in × $2.5 + 30M out × $15 | 5.30×gap |
| With caching90% of inputs cache-hit | $132no published cache discount | $58890M cached in × $1.25 + 10M in × $2.5 + 30M out × $15 | 4.45×gap |
Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.