Does prompt caching change whether Opus 4.8 or GPT-5.6 is cheaper?

Yes, it widens the gap in Opus's favor at the flagship tier. With prompt caching on the standard conversation, Claude Opus 4.8 drops to about $211.37 per 1,000 (a 52.2 percent total-cost cut) while GPT-5.6 Sol drops to about $236.38 (a 49.4 percent cut). Anthropic's caching claws back a slightly larger share, so cached Opus is about 11 percent cheaper than cached GPT-5.6 Sol, versus about 5 percent without caching. Caching never discounts output tokens on either provider.

Why is Claude Opus 4.8 cheaper than GPT-5.6 Sol if the input price is the same?

Because the standard conversation bills output too. Both models charge $5 per million input tokens, so the 63,500 input tokens cost $0.3175 on either. The gap is entirely output: Opus 4.8 charges $25 per million and GPT-5.6 Sol charges $30 per million, so the 5,000 output tokens cost $0.1250 on Opus versus $0.1500 on Sol. That $0.025 output difference per conversation is the whole $25 gap per 1,000 conversations.

What is the cheapest GPT-5.6 tier versus Claude Opus 4.8?

GPT-5.6 Luna is the cheapest GPT-5.6 tier at about $93.50 per 1,000 standard conversations ($1 input / $6 output per million), which is roughly 4.7x cheaper than Claude Opus 4.8 at $442.50. GPT-5.6 Terra sits in between at $233.75 per 1,000 ($2.50 input / $15 output), about 1.9x cheaper than Opus. These lighter tiers trade reasoning depth for price; compare them on your own task before switching.

Is per-token price a good way to compare GPT-5.6 and Claude Opus 4.8?

Not on its own. Per-token pricing hides that a multi-turn conversation resends its entire history every turn, so a 10-turn conversation bills 63,500 input tokens even though a single turn is only about 3,200. Comparing the full conversation cost, including the resent history and the output on every turn, is what tells you the real bill. That is why Opus 4.8 and GPT-5.6 Sol, which look far apart on some list rows, land within about 5 percent of each other on the standard conversation.

Cost comparison · real conversation, not per token · July 2026

GPT-5.6 vs Claude Opus 4.8: which is cheaper?

Q: Is GPT-5.6 cheaper than Claude Opus 4.8?

It depends on which GPT-5.6 tier. On a standard 10-turn conversation, flagship GPT-5.6 Sol costs $467.50 per 1,000 conversations while Claude Opus 4.8 costs $442.50, so Opus is about 5 percent cheaper than Sol. But the cheaper GPT-5.6 tiers undercut Opus: GPT-5.6 Terra is $233.75 per 1,000 (about 1.9x cheaper than Opus) and GPT-5.6 Luna is $93.50 per 1,000 (about 4.7x cheaper). So flagship-to-flagship Opus wins, but GPT-5.6 has cheaper options if you do not need top-tier reasoning. July 2026 list prices.

Q: GPT-5.6 vs Claude Opus 4.8 for chatbots: which costs less?

For a chatbot running the standard 10-turn conversation, both flagships share the same $5 per million input rate; the difference is output, where Claude Opus 4.8 charges $25 per million versus GPT-5.6 Sol at $30 per million. That makes Opus 4.8 about 5 percent cheaper per conversation ($0.4425 vs $0.4675). If your chatbot does not need flagship reasoning, GPT-5.6 Terra ($233.75 per 1,000) or a mid-tier Claude model like Sonnet 5 ($177 per 1,000) cuts the bill far more than the Opus-vs-Sol gap.

For a standard 10-turn conversation, Claude Opus 4.8 costs $442.50 per 1,000 conversations vs flagship GPT-5.6 Sol at $467.50 — Opus is ~5% cheaper as of July 2026, entirely on output pricing ($25 vs $30 / 1M). With prompt caching the gap widens to ~11% ($211.37 vs $236.38). But GPT-5.6's lighter tiers undercut Opus: Terra is ~1.9× cheaper and Luna ~4.7× cheaper.

Per-token price rows make these two look far apart. They are not — because a real conversation resends its whole history every turn, so both flagships bill the same 63,500 input tokens and differ only on output. Compared on the full conversation (the number that actually hits your invoice), Opus 4.8 edges out GPT-5.6 Sol. This page uses the real figures from our LLM Conversation Cost Index — no invented benchmarks.

OpenAI vs Anthropic · flagship tier Standard 10-turn conversation List prices verified July 13, 2026

$442.50

Claude Opus 4.8
per 1,000 conv

$467.50

GPT-5.6 Sol
per 1,000 conv

~5%

Opus cheaper
than Sol (no cache)

~11%

Opus cheaper
with caching

Head to head · flagship tier

Opus 4.8 vs GPT-5.6 Sol at a glance

The closest apples-to-apples comparison is the top reasoning model on each side. Both share the same $5 / 1M input rate; the entire difference is output price.

Anthropic · flagship reasoning

Claude Opus 4.8

$5.00 / 1M input · $25.00 / 1M output

$442.50

per 1,000 standard conversations

›$0.4425 per conversation
›$211.37 / 1,000 with prompt caching (52.2% off)
›Cheaper flagship on the standard conversation — ~5% under Sol, ~11% under with caching

OpenAI · flagship reasoning

GPT-5.6 Sol

$5.00 / 1M input · $30.00 / 1M output

$467.50

per 1,000 standard conversations

›$0.4675 per conversation
›$236.38 / 1,000 with prompt caching (49.4% off)
›Higher output rate ($30 vs $25 / 1M) is the whole gap — same input price

Full comparison

Every GPT-5.6 tier vs Claude Opus 4.8

GPT-5.6 ships in three tiers. Only the flagship (Sol) is pricier than Opus 4.8 — the mid and light tiers undercut it. Costs are the standard 10-turn conversation: 63,500 input tokens, 5,000 output tokens, full history resent every turn (see the math).

Model	Provider	Input $/1M	Output $/1M	Cost / conversation	Cost / 1,000 conv	With caching / 1,000 conv	vs Opus 4.8
GPT-5.6 Luna	OpenAI	$1.00	$6.00	$0.0935	$93.50	$47.27	4.7× cheaper
GPT-5.6 Terra	OpenAI	$2.50	$15.00	$0.2338	$233.75	$118.19	1.9× cheaper
Claude Opus 4.8	Anthropic	$5.00	$25.00	$0.4425	$442.50	$211.37	— baseline
GPT-5.6 Sol	OpenAI	$5.00	$30.00	$0.4675	$467.50	$236.38	5.6% pricier

All figures USD. "With caching" applies each provider's cache-read (0.1×) / cache-write (1.25×) rates to the stable prefix; output is never cached. Snapshot of published list prices, verified 2026-07-13. Full 11-model table: Conversation Cost Index.

Beyond price

When to choose each

Price is a tie-breaker, not the whole decision. On the standard conversation the flagship gap is only about 5% — small enough that quality, latency and ecosystem fit usually matter more than the $25-per-1,000 difference. This index measures cost only; it does not run quality or speed benchmarks, so treat the notes below as sourcing guidance, not scored claims.

Pick Claude Opus 4.8 when you want the cheaper flagship on multi-turn workloads, you are already caching (the gap widens to ~11%), or you prefer Anthropic's tooling and prompt-caching model. Its lower output rate ($25 vs $30 / 1M) compounds on output-heavy conversations.
Pick GPT-5.6 Sol when your evaluation on your own task favors it, or you are committed to OpenAI's ecosystem — the ~5% premium is often noise next to a real quality or integration advantage. Verify quality and latency yourself; we do not publish benchmark scores.
Don't need the flagship? The biggest savings aren't Opus-vs-Sol. Drop to GPT-5.6 Terra ($233.75 / 1,000, ~1.9× cheaper) or GPT-5.6 Luna ($93.50, ~4.7× cheaper), or a mid-tier Claude like Sonnet 5 ($177). A tier change dwarfs the flagship price gap.

Official list prices (always confirm — providers change them without notice): Anthropic pricing · Anthropic prompt caching · OpenAI pricing.

The math

Why the gap is exactly $25 / 1,000

An LLM API is stateless: to continue a conversation the client resends the full history as input every turn. The standard conversation fixes every variable — 2,000-token system prompt, 1,000-token tool block, 200 user + 500 assistant tokens per turn, 10 turns — which totals 63,500 input tokens and 5,000 output tokens. Both flagships charge the same $5 / 1M input, so the input bill is identical; only output differs.

Worked example · Claude Opus 4.8 vs GPT-5.6 Sol · standard 10-turn conversation

Shared input (both models, $5 / 1M)
  63,500 input tok x $5 / 1M        = $0.3175   (identical on both)

Output is the only difference
  Opus 4.8   5,000 out x $25 / 1M   = $0.1250
  GPT-5.6 Sol 5,000 out x $30 / 1M  = $0.1500

Cost per conversation
  Opus 4.8    = $0.3175 + $0.1250   = $0.4425  ->  $442.50 / 1,000
  GPT-5.6 Sol = $0.3175 + $0.1500   = $0.4675  ->  $467.50 / 1,000

Gap = $0.0250 / conversation = $25.00 / 1,000  (Sol 5.6% pricier)

With prompt caching (read 0.1x / write 1.25x on the prefix)
  Opus 4.8    -> $211.37 / 1,000   (52.2% total cut)
  GPT-5.6 Sol -> $236.38 / 1,000   (49.4% total cut)
  Cached gap  =  $25.01 / 1,000    (Opus ~11% cheaper)

Caveats. This is a planning index, not a bill. It assumes fixed average token sizes and a cache hit on every turn within the cache TTL, and uses standard synchronous list prices (no batch discounts, no context-length premiums). Reasoning/thinking tokens bill as output, which would push both flagships up together. Verify against your provider's usage dashboard.

Go deeper

Price your own numbers

Conversation Cost Simulator → Change turn count, token sizes and caching, and see Opus vs GPT-5.6 on your own conversation shape live. LLM Conversation Cost Index → The full 11-model table these figures come from — OpenAI, Anthropic, Google. Free CSV + JSON. Cheapest LLM for Chatbots → If price is your main lever, start here — the lowest-cost models for multi-turn chat, ranked.

FAQ

Common questions

Is GPT-5.6 cheaper than Claude Opus 4.8?+

It depends which GPT-5.6 tier. On the standard 10-turn conversation, flagship GPT-5.6 Sol is $467.50 per 1,000 vs Claude Opus 4.8 at $442.50 — so Opus is about 5% cheaper than Sol. But the lighter GPT-5.6 tiers undercut Opus: Terra is $233.75 (~1.9× cheaper) and Luna is $93.50 (~4.7× cheaper). Flagship-to-flagship Opus wins; if you don't need top-tier reasoning, GPT-5.6 has cheaper options.

GPT-5.6 vs Claude Opus 4.8 for chatbots: which costs less?+

For a chatbot on the standard conversation, both flagships share the same $5 / 1M input rate; the difference is output — Opus 4.8 at $25 / 1M vs GPT-5.6 Sol at $30 / 1M — making Opus about 5% cheaper ($0.4425 vs $0.4675 per conversation). If the bot doesn't need flagship reasoning, dropping to GPT-5.6 Terra ($233.75) or Claude Sonnet 5 ($177) saves far more than the Opus-vs-Sol gap.

Does prompt caching change which is cheaper?+

Yes — it widens the gap in Opus's favor at the flagship tier. Cached, Opus 4.8 drops to ~$211.37 / 1,000 (52.2% cut) while GPT-5.6 Sol drops to ~$236.38 (49.4% cut). Anthropic's caching claws back a slightly larger share, so cached Opus is about 11% cheaper than cached Sol, versus ~5% without caching. Caching never discounts output tokens on either provider.

Why is Opus 4.8 cheaper if the input price is the same?+

Because the conversation bills output too. Both charge $5 / 1M input, so the 63,500 input tokens cost $0.3175 on either. The gap is entirely output: Opus charges $25 / 1M and Sol charges $30 / 1M, so 5,000 output tokens cost $0.1250 vs $0.1500. That $0.025 output difference per conversation is the whole $25 gap per 1,000.

What's the cheapest GPT-5.6 tier vs Opus 4.8?+

GPT-5.6 Luna is cheapest at ~$93.50 per 1,000 standard conversations ($1 input / $6 output per 1M) — roughly 4.7× cheaper than Opus 4.8's $442.50. GPT-5.6 Terra sits between at $233.75 ($2.50 / $15), about 1.9× cheaper. These lighter tiers trade reasoning depth for price; test them on your own task before switching.

Is per-token price a good way to compare them?+

Not on its own. Per-token pricing hides that a multi-turn conversation resends its whole history every turn, so a 10-turn conversation bills 63,500 input tokens even though a single turn is ~3,200. Comparing the full conversation cost — resent history plus output on every turn — is what reveals the real bill, and it's why Opus 4.8 and GPT-5.6 Sol land within ~5% of each other.