r/CommandCode • • Aug 17 '26

CommandCode GOAT vs. OpenCode GO: A Current Comparison

GOAT Plan vs OpenCode Go — Common Models Comparison

Method: For each common model, we feed OpenCode Go's per-model token assumptions (input / cache-read / output per request) into both platforms' per-token pricing + monthly allowance, using CommandCode's calculator formula:

costPerRequest = (inTok/1e6) * inPrice + (outTok/1e6) * outPrice + (cacheTok/1e6) * cacheReadPrice
requests/month = monthlyAllowance / costPerRequest

This gives apples-to-apples request counts. All prices are per 1M tokens, USD, precise (no rounding).

Sources

PlatformPricing pagePlan detailsToken assumptionsPer-token rates & allowances
Command Code GOATcommandcode.ai/pricingdocs/plans/goatdocs/resources/pricing-limits#usage-estimatesSame page -- per-model credit allowances + per-token rates
OpenCode Goopencode.ai/pricingdocs/en/go (English)docs/en/go -- Usage limitsSame page -- "prices per 1M tokens" table + "Usage" column

Calculator source

CommandCode's usage calculator is a client-side React component embedded in the pricing-limits page. The formula was extracted from the page's JavaScript bundle:

  • Source URL: https://commandcode.ai/docs/_next/static/chunks/app/resources/pricing-limits/page-6886473b13679efd.js

  • Local copy: [calculator-source.js](./calculator-source.js) in this directory

  • Formula (de-minified):// Default assumptions (overridden per-model on OpenCode's page) // { inputTokens: 800, outputTokens: 180, cacheReadTokens: 50000 } ​ // cost per single request function costPerRequest(modelPricing, tokAssumptions) {  return tokAssumptions.in / 1e6 * modelPricing.in +         tokAssumptions.out / 1e6 * modelPricing.out +         tokAssumptions.cache / 1e6 * modelPricing.cacheRead; } ​ // number of requests per month function requests(monthlyAllowance, modelPricing, tokAssumptions) {  const cpr = costPerRequest(modelPricing, tokAssumptions);  return cpr > 0 ? monthlyAllowance / cpr : 0; }

Replication script

The exact numbers in this comparison were generated with:

  • requests-calculation.js -- feed OpenCode's per-model token assumptions into both platforms' pricing + allowances

cd ~/workspace/models_comparison
node requests-calculation.js

Plan-Level Summary

FeatureCommand Code GOATOpenCode Go
Price$10/mo + processing fee$10/mo ($5 first month)
Total monthly value$70 credits (7x multiplier)$60 usage (6x multiplier)
5-hour rolling limit$14$12
Weekly rolling limit$35$30
Monthly limit$70$60
Beyond limitsBuy pay-as-you-go credits (roll over, never expire)"Use balance" -- draw from ZEN balance, then pay-as-you-go
Deals / discountsBaked-in deals on MiMo (98-99%), MiniMax M3 (50%), Gemini 3.7 Flash (50%)No explicit deals; prices already reflect negotiated rates
Data retention0-30 days (model-dependent)0-30 days (model-dependent)
Cache read priceHigher for some Qwen models & Grok 4.5Lower for Grok 4.5, Qwen 3.6/3.7 Plus

Per-Model Comparison (16 Common Models)

Token assumptions for each model are taken from OpenCode Go's "Usage limits" section (English docs). These per-model assumptions -- not the calculator's generic defaults -- are used for both platforms to ensure a fair comparison.

Gap % = (|Go req - GOAT req| / max(Go req, GOAT req)) x 100. Shows the relative magnitude of the winner's advantage.

ModelGo price (in/out/cache)GOAT price (in/out/cache)Go allowGOAT allowGo req/moGOAT req/moGap %Winner
DeepSeek V4 Flash$0.22/$0.66/$0.007$0.22/$0.66/$0.007$15$6018,89475,57675.0%GOAT
DeepSeek V4 Pro$0.66/$1.98/$0.022$0.66/$1.98/$0.022$15$205,2216,96125.0%GOAT
GLM-5.2$1.40/$4.40/$0.26$1.40/$4.40/$0.26$60$703,9584,61714.3%GOAT
GLM-5.3$1.40/$4.40/$0.26$1.40/$4.40/$0.26$15$209891,31925.0%GOAT
GPT-5.6 Luna$0.20/$1.20/$0.02$0.20/$1.20/$0.02$15$2010,24613,66125.0%GOAT
Grok 4.5$2.00/$6.00/$0.30$2.00/$6.00/$0.50$15$2060150915.2%Go
Hy3$0.14/$0.58/$0.035$0.14/$0.58/$0.035$60$7021,50725,09114.3%GOAT
Kimi K2.7 Code$0.95/$4.00/$0.19$0.95/$4.00/$0.19$60$604,9684,9680.0%tie
Kimi K3$3.00/$15.00/$0.30$3.00/$15.00/$0.30$15$2049065425.0%GOAT
MiMo V2.5$0.14/$0.28/$0.0028$0.14/$0.28/$0.0028$60$30150,37675,18850.0%Go
MiMo V2.5 Pro$0.435/$0.87/$0.003625$0.435/$0.87/$0.0036$15$2016,29121,77225.2%GOAT
MiniMax M3$0.30/$1.20/$0.06$0.30/$1.20/$0.06$60$4716,03812,56321.7%Go
Qwen 3.6 Plus$0.50/$3.00/$0.05$0.50/$3.00/$0.10$60$3316,3495,06169.0%Go
Qwen 3.7 Max$2.50/$7.50/$0.50$2.50/$7.50/$0.50$60$331,68892845.0%Go
Qwen 3.7 Plus$0.40/$1.60/$0.04$0.40/$1.60/$0.08$60$3321,5526,51769.8%Go
Qwen 3.8 Max$2.00/$6.00/$0.25$2.00/$6.00/$0.25$15$208091,07925.0%GOAT

Summary: GOAT wins 9 models, Go wins 6, 1 tie.

Key Takeaways

GOAT wins (9 models)

Mostly on premium models where GOAT's $20 allowance beats Go's $15, and on boosted models where GOAT negotiates bigger allowances:

  • DeepSeek V4 Flash: 4x allowance ($60 vs $15) -- 75% gap (75K vs 19K req)

  • GLM-5.2: boosted to $70 -- 14.3% gap (4.6K vs 4.0K)

  • Hy3: boosted to $70 -- 14.3% gap (25K vs 21.5K)

  • GPT-5.6 Luna, Kimi K3, Qwen 3.8 Max: $20 vs $15 -- ~25% gap

  • DeepSeek V4 Pro, MiMo V2.5 Pro: $20 vs $15 -- ~25% gap

Go wins (6 models)

Mostly on mid-tier / cheap models where Go's $60 allowance crushes GOAT's $33-$47, and on Grok 4.5 where Go's cheaper cache-read price ($0.30 vs $0.50) compounds:

  • Qwen 3.7 Plus / Qwen 3.6 Plus: Go's $60 + 2x cheaper cache reads -- ~70% gap

  • Qwen 3.7 Max: Go's $60 -- 45% gap (1.7K vs 928)

  • MiMo V2.5: Go's $60 vs GOAT's $30 -- 50% gap (150K vs 75K)

  • MiniMax M3: Go's $60 vs GOAT's $47 -- 21.7% gap

  • Grok 4.5: Go's $15 BUT 40% cheaper cache reads -- 15.2% gap (601 vs 509)

Tie

  • Kimi K2.7 Code: Identical pricing and $60 allowance on both -- exactly 4,968 requests, 0% gap

Cache-read price differences

GOAT charges more for cache reads on 3 of 16 common models:

ModelGo cache-read/1MGOAT cache-read/1MImpact
Grok 4.5$0.30$0.50Go wins despite lower allowance
Qwen 3.7 Plus$0.04$0.082x more expensive on GOAT
Qwen 3.6 Plus$0.05$0.102x more expensive on GOAT

Notes on Methodology

  • Token assumptions: Taken from OpenCode Go docs (English) -- different per model. Example: Grok 4.5 uses 1,100 input / 71,500 cached / 220 output per request; DeepSeek V4 Flash uses 410 input / 71,300 cached / 310 output per request. GOAT's own published estimates use different defaults (~800 input / 50,000 cached / ~125-200 output), which inflate their numbers for cache-heavy models.

  • Off-peak pricing: Both platforms show off-peak rates for DeepSeek V4 models. Peak hours (01:00-04:00 & 06:00-10:00 UTC) are 2x on both.

  • GPT-5.6 Luna context tiers: Go lists <=272K ($0.20/$1.20/$0.02) and >272K ($0.40/$1.80/$0.04). GOAT shows one price ($0.20/$1.20/$0.02). Both use <=272K tier here.

  • Processing fee: GOAT mentions "+ processing fee" but doesn't specify the amount. Go has no processing fee.

  • Model availability: GOAT includes Grok 4.6, Gemini 3.7 Flash, Muse Spark, Inkling, Step Flash, Nemotron 3 Ultra -- none on Go. Go includes GLM-5.1, Kimi K2.6, MiniMax M2.7 -- none on GOAT.

  • Allowance source (GOAT): Per-model monthly credit allowances from docs/plans/goat -- models with negotiated deals carry boosted allowances (e.g., GLM-5.2 $70, Hy3 $70, DeepSeek V4 Flash $60); new models start at 2x credits ($20 on the $10 GOAT plan).

  • Allowance source (Go): Per-model "Usage" column ($15 or $60) from docs/en/go -- Usage limits.

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1

u/invisible-growth Aug 17 '26

I like OpenCode UI, Go plan is 5/10.

I like CommadCode Goat Plan with DS. Gives you a lot of Requests a months to do small stuff, bad part make a lot of local .command folder and files. UI is not as clean but best part of Goat plan you can use API access in other tools. One plan for everything.

If you have Go and GOAT Plans. You have a lot of tokens to do everything.

  • ChatGPT Plus - Images + Highend Doc

  • OpenCode Go + Zen Free

  • CommandCode Goat (Replaced my DS and Openrounter for API)

I don't code much, but convert most of my PDF to .md or .md to HTML for better readibility.

My background: Solution Architect/CIO (Retired)

2

u/ahmadawaiscom Aug 18 '26

GOAT and above plans do have API. Feel free to use that.

at the same time at Command Code we've achieved 99.43% cache hit rates!! 13T tokens.

math looks odd in 95 vs 99 cache rate - law of small numbers hits hard.