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Multimodal understanding (vision+)

Agents must reason over images/video/audio inputs at scale.

GET /api/decide?jtbd=multimodalAPI embedGoogle AI (Gemini) vs OpenAIGoogle AI (Gemini) vs Anthropic

At a glance — Oct 2026

Updated 2026-10-27 · forward this page: /jtbds/multimodal#brief

Scores as of 2026-10-19 (8 days old).

Depot Pick
Google AI (Gemini) · 8.43/10 for this job (curated estimate, high confidence)

capability multimodal + pricePerf. Gemini often wins value; OpenAI strong ecosystem.

Runner-up
OpenAI · 8.22/10

Scores higher than the pick on: Capability fit, Latency / reliability, Developer & agent DX, Maturity / track record.

When not to use the pick
Text-only coding agents — Anthropic; or OpenAI Realtime voice stacks.
Lock-in / migration
The pick has lower stored lock-in risk than runner-up OpenAI (6 vs 7.2). Self-host fallback listed for this job: Qwen2.5-VL-7B-Instruct, Florence-2-base, VisualWebArena.
Sourced price (usd_per_million_input_tokens)

Pick's lowest sourced SKU: gemini-3.5-flash-lite $0.3 (usd_per_million_input_tokens) — source, as of 2026-10-21

Cheapest matching SKU: Z.AI (Zhipu GLM) GLM-4.6V-FlashX $0.04 — source, as of 2026-10-03, re-checked 2026-10-27. Not the pick; not quality-adjusted.

Price history: first seen 2026-10-03 · last changed no change recorded · history JSON

Free option
  • Florence-2-base (oss) — source, as of 2026-10-25
  • Qwen2.5-VL-7B-Instruct (oss) — source, as of 2026-10-25
  • VisualWebArena (oss) — source, as of 2026-10-25
Failure modes to watch
  • Runaway spend: Set a budget and a tool-call cap per task. Alert when spend jumps. Stop the run at the cap instead of summarizing a partial trace as success.
Reported outcomes (submitted reports only)

This job: loading… JSON · reports never change scores · seed/test records excluded

Depot Pick (Google AI (Gemini)) on this job: loading… JSON · reports never change scores · seed/test records excluded

Same-job, same-unit comparisons: Google AI (Gemini) vs OpenAI · Google AI (Gemini) vs Anthropic · Google AI (Gemini) vs MiniMax · Google AI (Gemini) vs Z.AI (Zhipu GLM)

Cite: Agent Provider Depot, Depot Pick for multimodal: google-ai, scores as of 2026-10-19. Agents: GET /api/decide?jtbd=multimodal

Free Multimodal understanding (vision+) options · All sourced prices, cheapest first

Depot Pick

Google AI (Gemini)

capability multimodal + pricePerf. Gemini often wins value; OpenAI strong ecosystem.

Pricing (directional): Gemini 3.x Pro often ~$2/$12 under 200K; Flash tiers much cheaper. 1M context. Vertex for enterprise. Batch half-price common.

Cite: Depot Pick for multimodal: google-ai
Overall
8.4
curated_estimate
confidence: high · as of 2026-10-19
Capability fit
9.2
Price / performance
8.8
Latency / reliability
8.5
Developer & agent DX
8.2
Privacy / data retention
8.0
Lock-in risk (higher = worse)
6.0
Maturity / track record
9.6

Lock-in risk: higher = more lock-in (worse). Overall already inverts this dimension.

Sources: Google AI for Developers: https://ai.google.dev · Gemini API: https://ai.google.dev/gemini-api

Best value frontier stack and multimodal king. Use Flash for high-volume agent loops; Pro when quality matters. Prefer Vertex for enterprise compliance.

Quote for Multimodal understanding (vision+)

Depot Pick stays Google AI (Gemini). Prices below are sourced SKU rows only (as of 2026-10-27). Input and output are not blended. GET /api/quote?jtbd=multimodal

Pick is not a price winner. google-ai sourced input $/1M is 0.3; cheapest among candidates is zai at 0.04.

  • gemini-2.5-pro usd_per_million_input_tokens $2.5 source as of 2026-10-03
  • gemini-2.5-pro usd_per_million_input_tokens $1.25 source as of 2026-10-03
  • gemini-3-flash-preview usd_per_million_input_tokens $1 source as of 2026-10-03
  • gemini-3-flash-preview usd_per_million_input_tokens $0.5 source as of 2026-10-03
  • gemini-3.1-pro-preview usd_per_million_input_tokens $4 source as of 2026-10-03
  • gemini-3.1-pro-preview usd_per_million_input_tokens $2 source as of 2026-10-03
  • gemini-3.5-flash-lite (Batch) usd_per_million_input_tokens $0.15 source as of 2026-10-21
  • gemini-3.5-flash-lite usd_per_million_input_tokens $0.3 source as of 2026-10-21
  • gemini-3.8-flash usd_per_million_input_tokens $1.5 source as of 2026-10-03
  • gemini-3.8-flash usd_per_million_input_tokens $0.75 source as of 2026-10-03
  • gemini-2.5-pro usd_per_million_output_tokens $15 source as of 2026-10-03
  • gemini-2.5-pro usd_per_million_output_tokens $10 source as of 2026-10-03
  • gemini-3-flash-preview usd_per_million_output_tokens $3 source as of 2026-10-03
  • gemini-3.1-pro-preview usd_per_million_output_tokens $18 source as of 2026-10-03
  • gemini-3.1-pro-preview usd_per_million_output_tokens $12 source as of 2026-10-03
  • gemini-3.5-flash-lite (Batch) usd_per_million_output_tokens $1.25 source as of 2026-10-21
  • gemini-3.5-flash-lite usd_per_million_output_tokens $2.5 source as of 2026-10-21
  • gemini-3.8-flash usd_per_million_output_tokens $7.5 source as of 2026-10-03
  • gemini-3.8-flash usd_per_million_output_tokens $3.75 source as of 2026-10-03

1 of 7 candidates have no sourced price row. 1 are excluded from the Input $/1M comparison (chat_completion_input). min sourced input SKU among candidates; not quality-adjusted

Sourced Input $/1M for Multimodal understanding (vision+)

Candidates for this job that already have a matching sourced price (chat_completion_input), cheapest first. As of 2026-10-27. Each figure is one SKU in that unit, not a blend of input and output, not a cross-modal rate, and not a Depot score. min sourced input SKU among candidates; not quality-adjusted The Depot Pick is not a price winner.

ProviderInput $/1MSKUSourceAs of
Z.AI (Zhipu GLM)$0.04GLM-4.6V-FlashXpricing page2026-10-03
Anthropic$0.1Haiku 5.5 (prompts up to 100K tokens)pricing page2026-10-27
OpenAI$0.1gpt-6-lunapricing page2026-10-03
MiniMax$0.15MiniMax-M3.1-Flashpricing page2026-10-19
Google Vertex AI$0.25Gemini 3.1 Flash-Litepricing page2026-10-03
Google AI (Gemini)Depot Pick$0.3gemini-3.5-flash-litepricing page2026-10-21

Runners-up

OpenAI

Default when you want maximum capability and ecosystem glue. Multi-home critical paths behind OpenAI-compat…

8.2
llmfrontiermultimodaltools

Anthropic

Depot default for serious coding and production agents. Prefer Sonnet for cost/quality; reserve Opus for hard…

8.4
llmfrontiercodingagents

MiniMax

Primary indie-usable Chinese multimodal API alongside Moonshot. Prefer Anthropic/OpenAI for coding agents…

7.8
llmmultimodalttsvideo

Alibaba Cloud Model Studio (DashScope)

Catalog dashscope for Alibaba Model Studio / DashScope international Qwen. Complements Moonshot/MiniMax/Z.AI…

7.9
qwenalibabadashscopellm

Z.AI (Zhipu GLM)

International GLM via z.ai — catalog zai, not a second Zhipu mainland-only SKU. Strong cheap/coding runner…

7.8
glmzhipullmchina

When NOT to use the top pick

Text-only coding agents — Anthropic; or OpenAI Realtime voice stacks.

Full ranking (score table)

Ranked with this JTBD's weights. Scores are curated estimates unless marked otherwise. Agents: prefer /api/decide then this table for tie-breaks.

#ProviderOverallFit$/perfLatencyDXAs of
1Google AI (Gemini)Depot Pick8.49.28.88.58.22026-10-19
2Anthropic8.49.76.88.79.22026-10-19
3OpenAI8.29.66.28.89.52026-09-14
4Google Vertex AI8.09.07.09.07.22026-09-14
5Alibaba Cloud Model Studio (DashScope)7.98.68.28.47.22026-09-14
6MiniMax7.88.48.87.88.22026-09-14
7Z.AI (Zhipu GLM)7.88.29.07.68.02026-09-14

Score methodology for this job

capability multimodal + pricePerf. Gemini often wins value; OpenAI strong ecosystem.

  • capabilityFit: 25%
  • pricePerformance: 18%
  • latencyReliability: 15%
  • developerDx: 15%
  • privacyPosture: 10%
  • lockInRisk: 7%
  • maturity: 10%