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

GPT-5.6 Sol vs Doubao Seed Evolving

GPT-5.6 Sol wins on Overall, Coding; Doubao Seed Evolving wins on Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

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

Verdict at a glance

Bottom line: Choose GPT-5.6 Sol when coding depth matter most; choose Doubao Seed Evolving when lower cost, lower latency is the priority.

Choose GPT-5.6 Sol if you…

  • Enhanced reasoning
  • Strong code generation
  • o-series architecture
  • Best for: Reasoning-heavy tasks, Coding, Math

Choose Doubao Seed Evolving if you…

  • Continuously updated
  • 1M context
  • Good Chinese
  • ByteDance ecosystem
  • Best for: Chinese, Long context, Continuously evolving
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-5.6 Sol Higher overall
OpenAI · #11 overall
Overall72
Coding88
Multimodal80
VS
Doubao Seed Evolving
ByteDance · #15 overall
Overall68
Coding67
Multimodal83

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-5.6 SolDoubao Seed EvolvingVerdict
VendorOpenAI (US)ByteDance (CN)Different vendors
Released2026.072026.07Doubao Seed Evolving is newer
Overall (rank)72 · #1168 · #15GPT-5.6 Sol +4
Coding88 · #367 · #14GPT-5.6 Sol +21
Multimodal80 · #1183 · #9Doubao Seed Evolving +3
Context window1.05M1MGPT-5.6 Sol larger
Max output128K256KDoubao Seed Evolving longer
Effective-context8892Doubao Seed Evolving more reliable
Input $/1M$5$0.83Doubao Seed Evolving cheaper
Output $/1M$30$4.17Doubao Seed Evolving cheaper
Cache discount50% offcustomGPT-5.6 Sol deeper
Speed~25 tok/s~60 tok/sDoubao Seed Evolving faster
TTFT2.0s0.5sDoubao Seed Evolving snappier
Function calling9382GPT-5.6 Sol ahead
Refusal rate~14%~10%Doubao Seed Evolving less restrictive
English9270GPT-5.6 Sol
Chinese7493Doubao Seed Evolving
Modalitiestext, imagetext, imageSame
Open weightsNoNoBoth closed
Fine-tuningNoNo
Free tierNo free API tierDoubao App free
SOC2 / no-trainyes / yesno / yes
Private deploymentNoYesDoubao Seed Evolving

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-5.6 Sol leads the overall aggregate by 4 points (72 vs 68). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Doubao Seed Evolving remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a decisive gap: GPT-5.6 Sol scores 88 against 67. On multi-file edits, SWE-style tickets and long-horizon agent loops GPT-5.6 Sol needs fewer correction turns; Doubao Seed Evolving is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

Doubao Seed Evolving leads multimodal 83 vs 80. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

Doubao Seed Evolving is faster in interactive use: ~60 tok/s with 0.5s TTFT versus ~25 tok/s with 2.0s TTFT (about 2.4× 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-5.6 Sol and 1M for Doubao Seed Evolving. Crucially, the larger nominal window does not win on usable recall: GPT-5.6 Sol advertises 1.05M but Doubao Seed Evolving scores higher on effective-context (92 vs 88), i.e. it actually retains more of what it was given.

Price & total cost

Doubao Seed Evolving is the cheaper API at $0.83/$4.17 versus GPT-5.6 Sol at $5/$30 per 1M input/output tokens — list input is about 6.0× lower. Cache discounts (GPT-5.6 Sol 50%) shift the effective bill, worked out below.

Chinese vs English

English: GPT-5.6 Sol 92 vs Doubao Seed Evolving 70. Chinese: 74 vs 93. For Chinese-language production, Doubao Seed Evolving is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: GPT-5.6 Sol 93 vs Doubao Seed Evolving 82, so GPT-5.6 Sol has the edge on structured tool use. Neither offers standard fine-tuning. 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-5.6 SolDoubao Seed EvolvingGap
List priceno cache applied$1,400100M in × $5  +  30M out × $30$208100M in × $0.83  +  30M out × $4.176.73×gap
With caching90% of inputs cache-hit$1,17590M cached in × $2.5  +  10M in × $5  +  30M out × $30$208no published cache discount5.65×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-5.6 Sol (coding 88 vs 67).
IF you serve real-time users and latency is a product KPI  →  choose Doubao Seed Evolving (~60 tok/s, 0.5s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose Doubao Seed Evolving ($$0.83/$$4.17 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose Doubao Seed Evolving (effective context 92 vs 88).
07

Frequently asked questions

Is GPT-5.6 Sol worth the higher price over Doubao Seed Evolving?
At list the input rate is 6.0x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when GPT-5.6 Sol's stronger dimensions protect revenue; for routine volume Doubao Seed Evolving is the economical pick.
Which is better for agentic coding?
GPT-5.6 Sol is decisively stronger for coding (88 vs 67 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; Doubao Seed Evolving is fine for routine scripts.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, GPT-5.6 Sol is about $1,175/month and Doubao Seed Evolving about $208/month after cache discounts ($1,400 and $208 at list).
Does the bigger context window actually matter?
Nominal windows are GPT-5.6 Sol (1.05M) and Doubao Seed Evolving (1M), but usable recall follows the effective-context score (88 vs 92). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
Doubao Seed Evolving is the Chinese model (Chinese score 93, domestic cloud, possible private deployment) while GPT-5.6 Sol is the global model (Chinese 74, overseas API). Pick by language quality, access path and where data must reside.
What is the single-line recommendation?
Choose GPT-5.6 Sol for Reasoning-heavy tasks, Coding; choose Doubao Seed Evolving for Chinese, Long context.