Key Takeaways
- On list prices alone, Grok 4.5 costs 60% less on input and 76% less on output than Claude Opus 5 — $2/$6 against $5/$25 per million tokens.
- At identical token volumes, a 200-task-per-day coding pipeline runs about $936 a month on Grok 4.5 versus $3,300 on Opus 5, a saving near 72%.
- xAI reports Grok 4.5 resolving SWE-Bench Pro tasks in 15,954 output tokens on average against 67,020 for Opus 4.8 at max effort, which stretches the per-task gap toward 17x.
- That efficiency claim is vendor-reported, drawn from one benchmark, and compares against a deliberately verbose reasoning mode — treat it as a ceiling, not a forecast.
- Opus 4.8 still won SWE-Bench Pro 69.2% to 64.7%, while Grok 4.5 led Terminal-Bench 2.1 at 83.3% — the models split rather than one sweeping.
- Prompt caching narrows the gap sharply: Claude cache reads cost 10% of input, and the Batch API halves both directions.
- Claude Opus 5 runs adaptive thinking by default and bills thinking tokens as output, with developers reporting roughly 2x the output tokens of Opus 4.8 on matched tasks.
- Subscriptions can beat both API paths: one developer tracked 10 billion tokens over eight months at $15,000+ in API rates versus roughly $800 on a Claude Max plan.
Grok vs Claude Opus – artistic impression. Image credit: Alius Noreika / Google Gemini
Switching a coding workload from Claude Opus 5 to Grok 4.5 cuts your token bill by roughly 70% at equal token volumes, and by considerably more if xAI’s token-efficiency claims hold on your prompts. The list prices tell the first half of the story: $2 input and $6 output per million tokens on Grok 4.5, against $5 and $25 on Opus 5.
The second half is where the estimate gets slippery. Cost per completed task, not cost per token, is what a coding team actually pays — and that depends on how many tokens each model burns solving your tickets, how much of your context caches, and whether you are on API billing or a flat subscription. Below is the arithmetic for each of those, with the caveats attached where they belong.
The Sticker Price Comparison
Both models are current flagships. Claude Opus 5 arrived on 24 July 2026 at the same rates its predecessor carried, with a one-million-token window and no long-context premium. Grok 4.5 launched on 8 July 2026 with a 500,000-token window.
| Line item | Grok 4.5 | Claude Opus 5 |
|---|---|---|
| Input per 1M tokens | $2.00 | $5.00 |
| Output per 1M tokens | $6.00 | $25.00 |
| Cached input per 1M | $0.50 (reported) | $0.50 (documented 0.1x read rate) |
| Batch API | None listed | 50% off both directions ($2.50 / $12.50) |
| Fast or priority mode | 2x ($4 / $12) | 2x ($10 / $50) |
| Context window | 500,000 | 1,000,000 |
| Extra charges | $5 per 1,000 search tool calls | 1.1x multiplier for US-pinned inference |
On a blended three-to-one input-to-output mix, Grok 4.5 comes out roughly 3.3x cheaper per token. Opus 5 answers with a window twice the size and a batch discount Grok does not publish.
Three Ways to Model the Savings
Take a mid-sized agentic coding pipeline: 200 tasks a day, roughly 30,000 input and 16,000 output tokens per task. That is about 180M input and 96M output tokens a month. Three scenarios follow, and the spread between them is the whole point.
| Scenario | Grok 4.5 | Claude Opus 5 | Monthly saving |
|---|---|---|---|
| Equal tokens, list prices | ~$936 | ~$3,300 | ~$2,364 (72%) |
| Equal tokens, Opus with 90% cache hits on input | ~$936 | ~$2,490 | ~$1,554 (62%) |
| Vendor token-efficiency ratio applied to Opus output | ~$936 | ~$10,975 | ~$10,039 (91%) |
The third row uses xAI’s published figures: 15,954 output tokens per resolved SWE-Bench Pro task for Grok 4.5, against 67,020 for Opus 4.8 running at max effort. Priced out, that is roughly $0.10 per task against $1.68 — a 4.2x sticker gap on output turning into something near 17x per completed task, because a cheaper rate multiplies against fewer tokens.
Why the 17x figure needs discounting
Four reasons to shade it down. The token counts are vendor-reported. They come from a single benchmark. Opus at max effort is deliberately verbose, because extended reasoning is exactly how it earns its higher scores on harder evaluations — and it did win SWE-Bench Pro 69.2% to 64.7%. And the comparison is against Opus 4.8, not Opus 5, which runs adaptive thinking by default and bills every thinking token at the output rate. Developers running matched-effort tests have reported roughly double the output tokens of 4.8 on the same work, which cuts both ways: it makes the efficiency gap look larger and makes Opus 5 harder to budget for.
Even after heavy discounting, though, terse output compounds. Shorter responses cost less, stream faster, and shorten every loop in a multi-turn agent session.
What You Give Up Alongside the Savings
Cheaper is not the same as better, and the benchmark split makes that plain. Against Opus 4.8, Grok 4.5 took two wins and two losses on xAI’s own published charts: ahead on DeepSWE 1.0 and Terminal-Bench, behind on DeepSWE 1.1 and SWE-Bench Pro. The pattern is legible. Grok wins terminal-oriented, shell-driving, high-turn agentic evaluations. Opus wins the newer, messier, repository-scale ones that reward tracing a bug across many files before committing to a patch.
Claude Opus 5 pushed that further, debuting as the second model overall on the Senior SWE-Bench leaderboard behind Claude Fable 5, and posting the highest score of any evaluated model on the bug and performance investigation category. Independent trackers give Opus 5 the edge across the shared benchmarks it and Grok 4.5 both appear on.
The other trade-offs are practical. Grok 4.5’s 500K window is half of Opus 5’s, which matters for large codebase ingestion. Grok publishes no batch rate, so overnight bulk work loses a 50% discount you would get on Claude. And Grok’s cached-input pricing was still unconfirmed on xAI’s own docs page at launch, while Anthropic’s 0.1x cache-read rate is documented, with the minimum cacheable prefix dropped to 512 tokens on Opus 5 — meaning system prompts that were silently uncacheable before now cache without a code change. Anyone weighing model choice for day-to-day development will find the practical rankings in our tier list of the best LLMs for vibe coding useful alongside the price sheet.
The Route Most Teams Actually Take
Reports from the first weeks after Grok 4.5 shipped converged on a pattern that is neither “switch” nor “stay”: run both. Route terminal work, orchestration, and high-volume steps to Grok 4.5. Escalate to Opus for deep fault localisation and patch generation on the hard tickets. Gate every output behind your test suite. A tiered design spends premium tokens only where the difficulty is, and it typically lands the blended rate 30–40% under running everything on the expensive tier.
That approach also sidesteps the benchmark argument entirely. Public leaderboard numbers are not interchangeable when harnesses, prompts, compute budgets, and benchmark versions differ. The scorecard that matters is your own: total input and output tokens, tool calls, wall-clock time, retries, and cost per successfully completed ticket, scored by compilation and tests rather than by reading the diff.
Subscriptions Change the Maths Entirely
Before optimising per-token spend, check whether you should be paying per token at all. Claude Code draws from Claude subscription limits: Pro at $20 a month, Max 5x at $100, Max 20x at $200. One developer who tracked 10 billion tokens across eight months calculated over $15,000 at API rates against roughly $800 on the Max plan. Claude Code also caches aggressively — long sessions reuse the same repository context, so most input tokens bill at the cache-read rate.
On the xAI side, SuperGrok at $30 and SuperGrok Heavy at $300 cover interactive use, and both Grok Build and Cursor have included free Grok 4.5 access since launch. The API path is the right one for CI, automation, and anything programmatic. For interactive coding assistance, price both routes before defaulting to per-token billing.
The Short Answer
Budget for a 60–75% reduction if you swap Opus 5 for Grok 4.5 on a coding workload at comparable token volumes, and treat anything above that as upside you need to verify on your own prompts. The way to verify is unglamorous: run your real tickets through both models, read the usage object in each response, and compare cost per passing test rather than cost per million tokens. If Grok’s outputs on your prompts are not meaningfully shorter, the efficiency argument does not transfer, and you are left with the straightforward 3.3x price gap — which is still a large number. For context on how Anthropic’s recent Opus releases have traded capability against token consumption, our three-way comparison of Opus 4.6, 4.7 and 4.8 traces the pattern that Opus 5 continues.
Prices and benchmark figures are anchored to 28 July 2026 and drawn from vendor documentation and independent trackers. Model rates change frequently. This article is informational and not purchasing advice.
If you are interested in this topic, we suggest you check our articles:
- Best AI LLM for Vibe Coding: Complete 2026 Tier List
- Claude Opus 4.6 vs 4.7 vs 4.8: Which Model Wins?
- xAI vs OpenAI vs Anthropic: Which AI Lab Wins in 2026?
- Anthropic’s Claude Opus 4.6 Sets a New Bar for AI Capability
- 2026 AI Subscription Prices: Gemini vs ChatGPT vs Claude
Sources: Apidog, Apidog (Opus 5), Contra Collective, LLM Stats, BenchLM
Written by Alius Noreika
